Trial-to-trial variability and state-dependent modulation of auditory-evoked responses in cortex

Beyond task response-Pre-stimulus activity modulates contents of consciousness

The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).

Trial-by-trial variability in cortical responses exhibits scaling of spatial correlations predicted from critical dynamics

In the mammalian cortex, even simple sensory inputs or movements activate many neurons, with each neuron responding variably to repeated stimuli-a phenomenon known as trial-by-trial variability. Understanding the spatial patterns and dynamics of this variability is challenging. Using cellular 2-photon imaging, we study visual and auditory responses in the primary cortices of awake mice. We focus on how individual neurons' responses differed from the overall population. We find consistent spatial correlations in these differences that are unique to each trial and linearly scale with the cortical area observed, a characteristic of critical dynamics as confirmed in our neuronal simulations. Using chronic multi-electrode recordings, we observe similar scaling in the prefrontal and premotor cortex of non-human primates during self-initiated and visually cued motor tasks. These results suggest that trial-by-trial variability, rather than being random noise, reflects a critical, fluctuation-dominated state in the cortex, supporting the brain's efficiency in processing information.

First activity and interactions in thalamus and cortex using raw single-trial EEG and MEG elicited by somatosensory stimulation

Introduction

One of the primary motivations for studying the human brain is to comprehend how external sensory input is processed and ultimately perceived by the brain. A good understanding of these processes can promote the identification of biomarkers for the diagnosis of various neurological disorders; it can also provide ways of evaluating therapeutic techniques. In this work, we seek the minimal requirements for identifying key stages of activity in the brain elicited by median nerve stimulation.

Methods

We have used a priori knowledge and applied a simple, linear, spatial filter on the electroencephalography and magnetoencephalography signals to identify the early responses in the thalamus and cortex evoked by short electrical stimulation of the median nerve at the wrist. The spatial filter is defined first from the average EEG and MEG signals and then refined using consistency selection rules across ST. The refined spatial filter is then applied to extract the timecourses of each ST in each targeted generator. These ST timecourses are studied through clustering to quantify the ST variability. The nature of ST connectivity between thalamic and cortical generators is then studied within each identified cluster using linear and non-linear algorithms with time delays to extract linked and directional activities. A novel combination of linear and non-linear methods provides in addition discrimination of influences as excitatory or inhibitory.

Results

Our method identifies two key aspects of the evoked response. Firstly, the early onset of activity in the thalamus and the somatosensory cortex, known as the P14 and P20 in EEG and the second M20 for MEG. Secondly, good estimates are obtained for the early timecourse of activity from these two areas. The results confirm the existence of variability in ST brain activations and reveal distinct and novel patterns of connectivity in different clusters.

Discussion

It has been demonstrated that we can extract new insights into stimulus processing without the use of computationally costly source reconstruction techniques which require assumptions and detailed modeling of the brain. Our methodology, thanks to its simplicity and minimal computational requirements, has the potential for real-time applications such as in neurofeedback systems and brain-computer interfaces.

Developmental Exposure to Polychlorinated Biphenyls Prevents Recovery from Noise-Induced Hearing Loss and Disrupts the Functional Organization of the Inferior Colliculus

Exposure to combinations of environmental toxins is growing in prevalence; and therefore, understanding their interactions is of increasing societal importance. Here, we examined the mechanisms by which two environmental toxins, polychlorinated biphenyls (PCBs) and high-amplitude acoustic noise, interact to produce dysfunction in central auditory processing. PCBs are well established to impose negative developmental impacts on hearing. However, it is not known whether developmental exposure to this ototoxin alters the sensitivity to other ototoxic exposures later in life. Here, male mice were exposed to PCBs in utero, and later as adults were exposed to 45 min of high-intensity noise. We then examined the impacts of the two exposures on hearing and the organization of the auditory midbrain using two-photon imaging and analysis of the expression of mediators of oxidative stress. We observed that developmental exposure to PCBs blocked hearing recovery from acoustic trauma. In vivo two-photon imaging of the inferior colliculus (IC) revealed that this lack of recovery was associated with disruption of the tonotopic organization and reduction of inhibition in the auditory midbrain. In addition, expression analysis in the inferior colliculus revealed that reduced GABAergic inhibition was more prominent in animals with a lower capacity to mitigate oxidative stress. These data suggest that combined PCBs and noise exposure act nonlinearly to damage hearing and that this damage is associated with synaptic reorganization, and reduced capacity to limit oxidative stress. In addition, this work provides a new paradigm by which to understand nonlinear interactions between combinations of environmental toxins.SIGNIFICANCE STATEMENT Exposure to common environmental toxins is a large and growing problem in the population. This work provides a new mechanistic understanding of how the prenatal and postnatal developmental changes induced by polychlorinated biphenyls (PCBs) could negatively impact the resilience of the brain to noise-induced hearing loss (NIHL) later in adulthood. The use of state-of-the-art tools, including in vivo multiphoton microscopy of the midbrain helped in identifying the long-term central changes in the auditory system after the peripheral hearing damage induced by such environmental toxins. In addition, the novel combination of methods employed in this study will lead to additional advances in our understanding of mechanisms of central hearing loss in other contexts.

Unsupervised approach to decomposing neural tuning variability

Neural representation is often described by the tuning curves of individual neurons with respect to certain stimulus variables. Despite this tradition, it has become increasingly clear that neural tuning can vary substantially in accordance with a collection of internal and external factors. A challenge we are facing is the lack of appropriate methods to accurately capture the moment-to-moment tuning variability directly from the noisy neural responses. Here we introduce an unsupervised statistical approach, Poisson functional principal component analysis (Pf-PCA), which identifies different sources of systematic tuning fluctuations, moreover encompassing several current models (e.g.,multiplicative gain models) as special cases. Applying this method to neural data recorded from macaque primary visual cortex- a paradigmatic case for which the tuning curve approach has been scientifically essential- we discovered a simple relationship governing the variability of orientation tuning, which unifies different types of gain changes proposed previously. By decomposing the neural tuning variability into interpretable components, our method enables discovery of unexpected structure of the neural code, capturing the influence of the external stimulus drive and internal states simultaneously.

Developmental exposure to polychlorinated biphenyls prevents recovery from noise-induced hearing loss and disrupts the functional organization of the inferior colliculus

Exposure to combinations of environmental toxins is growing in prevalence, and therefore understanding their interactions is of increasing societal importance. Here, we examined the mechanisms by which two environmental toxins - polychlorinated biphenyls (PCBs) and high-amplitude acoustic noise - interact to produce dysfunction in central auditory processing. PCBs are well-established to impose negative developmental impacts on hearing. However, it is not known if developmental exposure to this ototoxin alters the sensitivity to other ototoxic exposures later in life. Here, male mice were exposed to PCBs in utero, and later as adults were exposed to 45 minutes of high-intensity noise. We then examined the impacts of the two exposures on hearing and the organization of the auditory midbrain using two-photon imaging and analysis of the expression of mediators of oxidative stress. We observed that developmental exposure to PCBs blocked hearing recovery from acoustic trauma. In vivo two-photon imaging of the inferior colliculus revealed that this lack of recovery was associated with disruption of the tonotopic organization and reduction of inhibition in the auditory midbrain. In addition, expression analysis in the inferior colliculus revealed that reduced GABAergic inhibition was more prominent in animals with a lower capacity to mitigate oxidative stress. These data suggest that combined PCBs and noise exposure act nonlinearly to damage hearing and that this damage is associated with synaptic reorganization, and reduced capacity to limit oxidative stress. In addition, this work provides a new paradigm by which to understand nonlinear interactions between combinations of environmental toxins.

Significance statement

Exposure to common environmental toxins is a large and growing problem in the population. This work provides a new mechanistic understanding of how the pre-and postnatal developmental changes induced by polychlorinated biphenyls could negatively impact the resilience of the brain to noise-induced hearing loss later in adulthood. The use of state-of-the-art tools, including in vivo multiphoton microscopy of the midbrain helped in identifying the long-term central changes in the auditory system after the peripheral hearing damage induced by such environmental toxins. In addition, the novel combination of methods employed in this study will lead to additional advances in our understanding of mechanisms of central hearing loss in other contexts.

Coupled Dynamics of Stimulus-Evoked Gustatory Cortical and Basolateral Amygdalar Activity

Gustatory cortical (GC) single-neuron taste responses reflect taste quality and palatability in successive epochs. Ensemble analyses reveal epoch-to-epoch firing-rate changes in these responses to be sudden, coherent transitions. Such nonlinear dynamics suggest that GC is part of a recurrent network, producing these dynamics in concert with other structures. Basolateral amygdala (BLA), which is reciprocally connected to GC and central to hedonic processing, is a strong candidate partner for GC, in that BLA taste responses evolve on the same general clock as GC and because inhibition of activity in the BLA→GC pathway degrades the sharpness of GC transitions. These facts motivate, but do not test, our overarching hypothesis that BLA and GC act as a single, comodulated network during taste processing. Here, we provide just this test of simultaneous (BLA and GC) extracellular taste responses in female rats, probing the multiregional dynamics of activity to directly test whether BLA and GC responses contain coupled dynamics. We show that BLA and GC response magnitudes covary across trials and within single responses, and that changes in BLA-GC local field potential phase coherence are epoch specific. Such classic coherence analyses, however, obscure the most salient facet of BLA-GC coupling: sudden transitions in and out of the epoch known to be involved in driving gaping behavior happen near simultaneously in the two regions, despite huge trial-to-trial variability in transition latencies. This novel form of inter-regional coupling, which we show is easily replicated in model networks, suggests collective processing in a distributed neural network.SIGNIFICANCE STATEMENT There has been little investigation into real-time communication between brain regions during taste processing, a fact reflecting the dominant belief that taste circuitry is largely feedforward. Here, we perform an in-depth analysis of real-time interactions between GC and BLA in response to passive taste deliveries, using both conventional coherence metrics and a novel methodology that explicitly considers trial-to-trial variability and fast single-trial dynamics in evoked responses. Our results demonstrate that BLA-GC coherence changes as the taste response unfolds, and that BLA and GC specifically couple for the sudden transition into (and out of) the behaviorally relevant neural response epoch, suggesting (although not proving) that: (1) recurrent interactions subserve the function of the dyad as (2) a putative attractor network.

Visual evoked feedforward-feedback traveling waves organize neural activity across the cortical hierarchy in mice

Sensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. Neuronal oscillations have been shown to mediate intercortical feedforward and feedback interactions. Yet, the macroscopic structure of the multitude of such oscillations remains unclear. Here, we show that simple visual stimuli reliably evoke two traveling waves with spatial wavelengths that cover much of the cerebral hemisphere in awake mice. 30-50 Hz feedforward waves arise in primary visual cortex (V1) and propagate rostrally, while 3-6 Hz feedback waves originate in the association cortex and flow caudally. The phase of the feedback wave modulates the amplitude of the feedforward wave and synchronizes firing between V1 and parietal cortex. Altogether, these results provide direct experimental evidence that visual evoked traveling waves percolate through the cerebral cortex and coordinate neuronal activity across broadly distributed networks mediating visual processing.

Non-additive activity modulation during a decision making task involving tactic selection

Human brain imaging has revealed that stimulus-induced activity does generally not simply add to the pre-stimulus activity, but rather builds in a non-additive way on this activity. Here we investigate this subject at the single neuron level and address the question whether and to what extent a strong form of non-additivity where activity drops post-cue is present in different areas of monkey cortex, including prefrontal and agranular frontal areas, during a perceptual decision making task involving action and tactic selection. Specifically we analyze spike train data recorded in vivo from the posterior dorsomedial prefrontal cortex (pmPFC), the supplementary motor area (SMA) and the presupplementary motor area (pre-SMA). For each neuron, we compute the ratio of the trial-averaged pre-stimulus spike count to the trial-averaged post-stimulus count. We also perform the ratio and averaging procedures in reverse order. We find that the statistics of these quantities behave differently across areas. pmPFC involved in tactic selection shows stronger non-additivity compared to the two other areas which more generically just increase their firing rate pos-stimulus. pmPFC behaved more similarly to pre-SMA, a likely consequence of the reciprocal connections between these areas. The trial-averaged ratio statistic was reproduced by a surrogate inhomogeneous Poisson process in which the measured trial-averaged firing rate for a given neuron is used as its time-dependent rate. Principal component analysis (PCA) of the trial-averaged firing rates of neuronal ensembles further reveals area-specific time courses of response to the stimulus, including latency to peak neural response, for the typical population activity. Our work demonstrates subtle forms of area-specific non-additivity based on the fine variability structure of pre- and post-stimulus spiking activity on the single neuron level. It also reveals significant differences between areas for PCA and surrogate analysis, complementing previous observations of regional differences based solely on post-stimulus responses. Moreover, we observe regional differences in non-additivity which are related to the monkey's successful tactic selection and decision making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-021-09702-0.

Multiple states in ongoing neural activity in the rat visual cortex

The brain continuously produces internal activity in the absence of afferently salient sensory input. Spontaneous neural activity is intrinsically defined by circuit structures and associated with the mode of information processing and behavioral responses. However, the spatiotemporal dynamics of spontaneous activity in the visual cortices of behaving animals remain almost elusive. Using a custom-made electrode array, we recorded 32-site electrocorticograms in the primary and secondary visual cortex of freely behaving rats and determined the propagation patterns of spontaneous neural activity. Nonlinear dimensionality reduction and unsupervised clustering revealed multiple discrete states of the activity patterns. The activity remained stable in one state and suddenly jumped to another state. The diversity and dynamics of the internally switching cortical states would imply flexibility of neural responses to various external inputs.

Cortical Responses to Vowel Sequences in Awake and Anesthetized States: A Human Intracranial Electrophysiology Study

Elucidating neural signatures of sensory processing across consciousness states is a major focus in neuroscience. Noninvasive human studies using the general anesthetic propofol reveal differential effects on auditory cortical activity, with a greater impact on nonprimary and auditory-related areas than primary auditory cortex. This study used intracranial electroencephalography to examine cortical responses to vowel sequences during induction of general anesthesia with propofol. Subjects were adult neurosurgical patients with intracranial electrodes placed to identify epileptic foci. Data were collected before electrode removal surgery. Stimuli were vowel sequences presented in a target detection task during awake, sedated, and unresponsive states. Averaged evoked potentials (AEPs) and high gamma (70-150 Hz) power were measured in auditory, auditory-related, and prefrontal cortex. In the awake state, AEPs were found throughout studied brain areas; high gamma activity was limited to canonical auditory cortex. Sedation led to a decrease in AEP magnitude. Upon LOC, there was a decrease in the superior temporal gyrus and adjacent auditory-related cortex and a further decrease in AEP magnitude in core auditory cortex, changes in the temporal structure and increased trial-to-trial variability of responses. The findings identify putative biomarkers of LOC and serve as a foundation for future investigations of altered sensory processing.

Prestimulus dynamics blend with the stimulus in neural variability quenching

Neural responses to the same stimulus show significant variability over trials, with this variability typically reduced (quenched) after a stimulus is presented. This trial-to-trial variability (TTV) has been much studied, however how this neural variability quenching is influenced by the ongoing dynamics of the prestimulus period is unknown. Utilizing a human intracranial stereo-electroencephalography (sEEG) data set, we investigate how prestimulus dynamics, as operationalized by standard deviation (SD), shapes poststimulus activity through trial-to-trial variability (TTV). We first observed greater poststimulus variability quenching in those real trials exhibiting high prestimulus variability as observed in all frequency bands. Next, we found that the relative effect of the stimulus was higher in the later (300-600ms) than the earlier (0-300ms) poststimulus period. Lastly, we replicate our findings in a separate EEG dataset and extend them by finding that trials with high prestimulus variability in the theta and alpha bands had faster reaction times. Together, our results demonstrate that stimulus-related activity, including its variability, is a blend of two factors: 1) the effects of the external stimulus itself, and 2) the effects of the ongoing dynamics spilling over from the prestimulus period - the state at stimulus onset - with the second dwarfing the influence of the first.

Endogenous activity modulates stimulus and circuit-specific neural tuning and predicts perceptual behavior

Perception reflects not only sensory inputs, but also the endogenous state when these inputs enter the brain. Prior studies show that endogenous neural states influence stimulus processing through non-specific, global mechanisms, such as spontaneous fluctuations of arousal. It is unclear if endogenous activity influences circuit and stimulus-specific processing and behavior as well. Here we use intracranial recordings from 30 pre-surgical epilepsy patients to show that patterns of endogenous activity are related to the strength of trial-by-trial neural tuning in different visual category-selective neural circuits. The same aspects of the endogenous activity that relate to tuning in a particular neural circuit also correlate to behavioral reaction times only for stimuli from the category that circuit is selective for. These results suggest that endogenous activity can modulate neural tuning and influence behavior in a circuit- and stimulus-specific manner, reflecting a potential mechanism by which endogenous neural states facilitate and bias perception.

Spontaneous network activity <35 ​Hz accounts for variability in stimulus-induced gamma responses

Gamma activity is thought to serve several cognitive processes, including attention and memory. Even for the simplest stimulus, the occurrence of gamma activity is highly variable, both within and between individuals. The sources of this variability, however, are largely unknown. In this paper, we address one possible cause: the cross-frequency influence of spontaneous, whole-brain network activity on visual stimulus processing. By applying Hidden Markov modelling to MEG data, we reveal that the trial-averaged gamma response to a moving grating depends on the individual network dynamics, inferred from slower brain activity (<35 ​Hz) in the absence of stimulation (resting-state and task baseline). In addition, we demonstrate that modulations of network activity in task baseline influence the gamma response on the level of trials. In summary, our results reveal a cross-frequency and cross-session association between gamma responses induced by visual stimulation and spontaneous network activity. These findings underline the dependency of visual stimulus processing on the individual, functional network architecture.

Interactions between stimuli-evoked cortical activity and spontaneous low frequency oscillations measured with neuronal calcium

Spontaneous brain activity has been widely used to map brain connectivity. The interactions between task-evoked brain responses and the spontaneous cortical oscillations, especially within the low frequency range of ~0.1 ​Hz, are not fully understood. Trial-to-trial variabilities in brain's response to sensory stimuli and the ability for brain to detect under noisy conditions suggest an appreciable impact of the brain state. Using a multimodality imaging platform, we simultaneously imaged neuronal Ca²⁺ and cerebral hemodynamics at baseline and in response to single-pulse forepaw stimuli in rat's somatosensory cortex. The high sensitivity of this system enables detection of responses to very weak and strong stimuli and real time determination of low frequency oscillations without averaging. Results show that the ongoing neuronal oscillations inversely modulate Ca²⁺ transients evoked by sensory stimuli. High intensity stimuli reset the spontaneous neuronal oscillations to an unpreferable excitability following the stimulus. Cerebral hemodynamic responses also inversely interact with the spontaneous hemodynamic oscillations, correlating with the neuronal Ca²⁺ transient changes. The results reveal competing interactions between spontaneous oscillations and stimulation-evoked brain activities in somatosensory cortex and the resultant hemodynamics.

Emergence of spatially periodic diffusive waves in small-world neuronal networks

It has been observed in experiment that the anatomical structure of neuronal networks in the brain possesses the feature of small-world networks. Yet how the small-world structure affects network dynamics remains to be fully clarified. Here we study the dynamics of a class of small-world networks consisting of pulse-coupled integrate-and-fire (I&F) neurons. Under stochastic Poisson drive, we find that the activity of the entire network resembles diffusive waves. To understand its underlying mechanism, we analyze the simplified regular-lattice network consisting of firing-rate-based neurons as an approximation to the original I&F small-world network. We demonstrate both analytically and numerically that, with strongly coupled connections, in the absence of noise, the activity of the firing-rate-based regular-lattice network spatially forms a static grating pattern that corresponds to the spatial distribution of the firing rate observed in the I&F small-world neuronal network. We further show that the spatial grating pattern with different phases comprise the continuous attractor of both the I&F small-world and firing-rate-based regular-lattice network dynamics. In the presence of input noise, the activity of both networks is perturbed along the continuous attractor, which gives rise to the diffusive waves. Our numerical simulations and theoretical analysis may potentially provide insights into the understanding of the generation of wave patterns observed in cortical networks.

Fast Electrophysiological Mapping of Rat Cortical Motor Representation on a Time Scale of Minutes during Skin Stimulation

The topographic map of motor cortical representation, called the motor map, is not invariant, but can be altered by motor learning, neurological injury, and functional recovery from injury. Although much attention has been paid to short-term changes of the motor map, robust measures have not been established. The existing mapping methods are time-consuming, and the obtained maps are confounded by time preference. The purpose of this study was to examine the dynamics of the motor map on a timescale of minutes during transient somatosensory input by a fast motor mapping technique. We applied 32-channel micro-electrocorticographic electrode arrays to the rat sensorimotor cortex for cortical stimulation, and the topographic profile of motor thresholds in forelimb muscle was identified by fast motor mapping. Sequential motor maps were obtained every few minutes before, during, and just after skin stimulation to the dorsal forearm using a wool buff. During skin stimulation, the motor map expanded and the center of gravity of the map was shifted caudally. The expansion of the map persisted for at least a few minutes after the end of skin stimulation. Although the motor threshold of the hotspot was not changed, the area in which it was decreased appeared caudally to the hotspot, which may be in the somatosensory cortex. The present study demonstrated rapid enlargement of the forelimb motor map in the order of a few minutes induced by skin stimulation. This helps to understand the spatial dynamism of motor cortical representation that is modulated rapidly by somatosensory input.

Two-Color Volumetric Imaging of Neuronal Activity of Cortical Columns

To capture the emergent properties of neural circuits, high-speed volumetric imaging of neural activity at cellular resolution is needed. Here, we introduce wavelength multiplexing to perform fast volumetric two-photon imaging of cortical columns (>2,000 neurons in 10 planes at 10 vol/s), using two different calcium indicators, an electrically tunable lens and a spatial light modulator. We image the activity of neuronal populations from layers 2/3 to 5 of primary visual cortex from awake mice, finding a lack of columnar structures in orientation responses and revealing correlations between layers which differ from trial to trial. We also simultaneously image functional correlations between presynaptic layer 1 axons and postsynaptic layer 2/3 neurons. Wavelength multiplexing enhances high-speed volumetric microscopy and can be combined with other optical multiplexing methods to easily boost imaging throughput.

Disruption of cortical network activity by the general anaesthetic isoflurane

Background

Actions of general anaesthetics on activity in the cortico-thalamic network likely contribute to loss of consciousness and disconnection from the environment. Previously, we showed that the general anaesthetic isoflurane preferentially suppresses cortically evoked synaptic responses compared with thalamically evoked synaptic responses, but how this differential sensitivity translates into changes in network activity is unclear.

Methods

We investigated isoflurane disruption of spontaneous and stimulus-induced cortical network activity using multichannel recordings in murine auditory thalamo-cortical brain slices.

Results

Under control conditions, afferent stimulation elicited short latency, presumably monosynaptically driven, spiking responses, as well as long latency network bursts that propagated horizontally through the cortex. Isoflurane (0.05-0.6 mM) suppressed spiking activity overall, but had a far greater effect on network bursts than on early spiking responses. At isoflurane concentrations >0.3 mM, network bursts were almost entirely blocked, even with increased stimulation intensity and in response to paired (thalamo-cortical + cortical layer 1) stimulation, while early spiking responses were <50% blocked. Isoflurane increased the threshold for eliciting bursts, decreased their propagation speed and prevented layer 1 afferents from facilitating burst induction by thalamo-cortical afferents.

Conclusions

Disruption of horizontal activity spread and of layer 1 facilitation of thalamo-cortical responses likely contribute to the mechanism by which suppression of cortical feedback connections disrupts sensory awareness under anaesthesia.

Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements

Neural circuits are able to perform computations under very diverse conditions and requirements. The required computations impose clear constraints on their fine-tuning: a rapid and maximally informative response to stimuli in general requires decorrelated baseline neural activity. Such network dynamics is known as asynchronous-irregular. In contrast, spatio-temporal integration of information requires maintenance and transfer of stimulus information over extended time periods. This can be realized at criticality, a phase transition where correlations, sensitivity and integration time diverge. Being able to flexibly switch, or even combine the above properties in a task-dependent manner would present a clear functional advantage. We propose that cortex operates in a “reverberating regime” because it is particularly favorable for ready adaptation of computational properties to context and task. This reverberating regime enables cortical networks to interpolate between the asynchronous-irregular and the critical state by small changes in effective synaptic strength or excitation-inhibition ratio. These changes directly adapt computational properties, including sensitivity, amplification, integration time and correlation length within the local network. We review recent converging evidence that cortex in vivo operates in the reverberating regime, and that various cortical areas have adapted their integration times to processing requirements. In addition, we propose that neuromodulation enables a fine-tuning of the network, so that local circuits can either decorrelate or integrate, and quench or maintain their input depending on task. We argue that this task-dependent tuning, which we call “dynamic adaptive computation,” presents a central organization principle of cortical networks and discuss first experimental evidence.

State dependence of stimulus-induced variability tuning in macaque MT

Behavioral states marked by varying levels of arousal and attention modulate some properties of cortical responses (e.g. average firing rates or pairwise correlations), yet it is not fully understood what drives these response changes and how they might affect downstream stimulus decoding. Here we show that changes in state modulate the tuning of response variance-to-mean ratios (Fano factors) in a fashion that is neither predicted by a Poisson spiking model nor changes in the mean firing rate, with a substantial effect on stimulus discriminability. We recorded motion-sensitive neurons in middle temporal cortex (MT) in two states: alert fixation and light, opioid anesthesia. Anesthesia tended to lower average spike counts, without decreasing trial-to-trial variability compared to the alert state. Under anesthesia, within-trial fluctuations in excitability were correlated over longer time scales compared to the alert state, creating supra-Poisson Fano factors. In contrast, alert-state MT neurons have higher mean firing rates and largely sub-Poisson variability that is stimulus-dependent and cannot be explained by firing rate differences alone. The absence of such stimulus-induced variability tuning in the anesthetized state suggests different sources of variability between states. A simple model explains state-dependent shifts in the distribution of observed Fano factors via a suppression in the variance of gain fluctuations in the alert state. A population model with stimulus-induced variability tuning and behaviorally constrained information-limiting correlations explores the potential enhancement in stimulus discriminability by the cortical population in the alert state.

The brain controls behavior fluidly in a wide variety of cognitive contexts that alter the precision of neural responses. We examine how neural variability changes versus the mean response as a function of the stimulus and the behavioral state. We show that this scaled variability can have qualitatively different stimulus tuning in different behavioral contexts. In alert primates, scaled variability is tuned to the direction of motion of a visual stimulus and decreases around the preferred direction of each neuron. Under anesthesia, neurons show flat scaled variability tuning and, overall, responses are significantly more variable. We develop a simple model that includes a parameter describing firing rate gain fluctuations that can explain these changes. Our results suggest that tuned decreases in scaled variability during wakefulness may be mediated by an active process that suppresses synchronization and makes information transmission more reliable.

Linear-nonlinear-time-warp-poisson models of neural activity

Prominent models of spike trains assume only one source of variability - stochastic (Poisson) spiking - when stimuli and behavior are fixed. However, spike trains may also reflect variability due to internal processes such as planning. For example, we can plan a movement at one point in time and execute it at some arbitrary later time. Neurons involved in planning may thus share an underlying time course that is not precisely locked to the actual movement. Here we combine the standard Linear-Nonlinear-Poisson (LNP) model with Dynamic Time Warping (DTW) to account for shared temporal variability. When applied to recordings from macaque premotor cortex, we find that time warping considerably improves predictions of neural activity. We suggest that such temporal variability is a widespread phenomenon in the brain which should be modeled.

A mathematical model to mimic the shape of event related desynchronization/synchronization

Rhythmic oscillatory activities of the sensory cortex have been observed after a presentation of a stimulus. This activity first drops dramatically and then increases considerably that are respectively named event-related desynchronization (ERD) and event-related synchronization (ERS). There are several effective factors that can alter the ERD and ERS pattern. In this study, a mathematical model was presented that produced ERD and ERS pattern in response to a stimulus. This model works based on the synchronization concepts. The proposed model provided different suggestions about the reason behind the relationship between the encoding of incoming sensory information and the oscillatory activities, effective factors on the characteristics of neuronal units, and how may these factors affect the amplitude and latency of the ERD and ERS.

Altered stimulus representation in rat auditory cortex is not causal for loss of consciousness under general anaesthesia

BACKGROUND

Current concepts suggest that impaired representation of information in cortical networks contributes to loss of consciousness under anaesthesia. We tested this idea in rat auditory cortex using information theory analysis of multiunit responses recorded under three anaesthetic agents with different molecular targets: isoflurane, propofol, and dexmedetomidine. We reasoned that if changes in the representation of sensory stimuli are causal for loss of consciousness, they should occur regardless of the specific anaesthetic agent.

METHODS

Spiking responses were recorded with chronically implanted microwire arrays in response to acoustic stimuli incorporating varied temporal and spectral dynamics. Experiments consisted of four drug conditions: awake (pre-drug), sedation (i.e. intact righting reflex), loss of consciousness (a dose just sufficient to cause loss of righting reflex), and recovery. Measures of firing rate, spike timing, and mutual information were analysed as a function of drug condition.

RESULTS

All three drugs decreased spontaneous and evoked spiking activity and modulated spike timing. However, changes in mutual information were inconsistent with altered stimulus representation being causal for loss of consciousness. First, direction of change in mutual information was agent-specific, increasing under dexmedetomidine and decreasing under isoflurane and propofol. Second, mutual information did not decrease at the transition between sedation and LOC for any agent. Changes in mutual information under anaesthesia correlated strongly with changes in precision and reliability of spike timing, consistent with the importance of temporal stimulus features in driving auditory cortical activity.

CONCLUSIONS

The primary sensory cortex is not the locus for changes in representation of information causal for loss of consciousness under anaesthesia.

Beyond the evoked/intrinsic neural process dichotomy

Contemporary functional neuroimaging research has increasingly focused on characterization of intrinsic or "spontaneous" brain activity. Analysis of intrinsic activity is often contrasted with analysis of task-evoked activity that has traditionally been the focus of cognitive neuroscience. But does this evoked/intrinsic dichotomy adequately characterize human brain function? Based on empirical data demonstrating a close functional interdependence between intrinsic and task-evoked activity, we argue that the dichotomy between intrinsic and task-evoked activity as unobserved contributions to brain activity is artificial. We present an alternative picture of brain function in which the brain's spatiotemporal dynamics do not consist of separable intrinsic and task-evoked components, but reflect the enaction of a system of mutual constraints to move the brain into and out of task-appropriate functional configurations. According to this alternative picture, cognitive neuroscientists are tasked with describing both the temporal trajectory of brain activity patterns across time, and the modulation of this trajectory by task states, without separating this process into intrinsic and task-evoked components. We argue that this alternative picture of brain function is best captured in a novel explanatory framework called enabling constraint. Overall, these insights call for a reconceptualization of functional brain activity, and should drive future methodological and empirical efforts.

Frequency selectivity of echo responses in the mouse primary auditory cortex

In the primary auditory cortex (A1), neuronal ensembles are activated relative to anticipated sound events following rhythmic stimulation, but whether the echo responses of the neurons are related to their frequency selectivity remains unknown. Therefore, we used in vivo two-photon Ca²⁺ imaging to record the neuronal activities in the mouse A1 to elucidate the relationship between their echo responses and frequency selectivity. We confirmed the presence of echo responses in a subgroup of mouse Layer 2/3 A1 neurons following a train of rhythmic pure tone stimulation. After testing with a range of frequencies, we found that these echo responses occurred preferentially close to the best frequencies of the neurons. The local organization of the echo responses of the neurons was heterogeneous in the A1. Therefore, these results indicate that the observed echo responses of neurons within A1 are highly related to their frequency selectivity.

Sleep- and Wake-Like States in Small Networks In Vivo and In Vitro

Wakefulness and sleep are highly complex and heterogeneous processes, involving multiple neurotransmitter systems and a sophisticated interplay between global and local networks of neurons and non-neuronal cells. Macroscopic approaches applied at the level of the whole organism, view sleep as a global behaviour and allow for investigation into aspects such as the effects of insufficient or disrupted sleep on cognitive function, metabolism, thermoregulation and sensory processing. While significant progress has been achieved using such large-scale approaches, the inherent complexity of sleep-wake regulation has necessitated the development of methods which tackle specific aspects of sleep in isolation. One way this may be achieved is by investigating specific cellular or molecular phenomena in the whole organism in situ, either during spontaneous or induced sleep-wake states. This approach has greatly advanced our knowledge about the electrophysiology and pharmacology of ion channels, specific receptors, intracellular pathways and the small networks implicated in the control and regulation of the sleep-wake cycle. Importantly though, there are a variety of external and internal factors that influence global behavioural states which are difficult to control for using these approaches. For this reason, over the last few decades, ex vivo experimental models have become increasingly popular and have greatly advanced our understanding of many fundamental aspects of sleep, including the neuroanatomy and neurochemistry of sleep states, sleep regulation, the origin and dynamics of specific sleep oscillations, network homeostasis as well as the functional roles of sleep. This chapter will focus on the use of small neuronal networks as experimental models and will highlight the most significant and novel insights these approaches have provided.

Local field potentials are induced by visually evoked spiking activity in macaque cortical area MT

Local field potentials (LFP) have been the focus of many recent studies in systems neuroscience. However, the exact neural basis of these signals remains unclear. To address this question, we determined the relationship between LFP signals and another, much better understood, signature of neural activity: action potentials. Specifically, we focused on the relationship between the amplitude of stimulus-induced LFPs and the magnitude of spiking activity in visual cortex of non-human primates. Our trial-by-trial correlation analyses between these two components of extracellular signals in macaque visual cortex show that the spike rate is coupled to the LFP amplitude with a surprisingly long latency, typically 50 ms. Our analysis shows that the neural spike rate is a significant predictor of the LFP amplitude. This limits the functional interpretation of LFP signals beyond that based on spiking activities.

The Impact of Anesthetic State on Spike-Sorting Success in the Cortex: A Comparison of Ketamine and Urethane Anesthesia

Spike sorting is an essential first step in most analyses of extracellular in vivo electrophysiological recordings. Here we show that spike-sorting success depends critically on characteristics of coordinated population activity that can differ between anesthetic states. In tetrode recordings from mouse auditory cortex, spike sorting was significantly less successful under ketamine/medetomidine (ket/med) than urethane anesthesia. Surprisingly, this difficulty with sorting under ket/med anesthesia did not appear to result from either greater millisecond-scale burstiness of neural activity or increased coordination of activity among neighboring neurons. Rather, the key factor affecting sorting success appeared to be the amount of coordinated population activity at long time intervals and across large cortical distances. We propose that spike-sorting success is directly dependent on overall coordination of activity, and is most disrupted by large-scale fluctuations in cortical population activity. Reliability of single-unit recording may therefore differ not only between urethane-anesthetized and ket/med-anesthetized states as demonstrated here, but also between synchronized and desynchronized states, asleep and awake states, or inattentive and attentive states in unanesthetized animals.

CS-specific modifications of auditory evoked potentials in the behaviorally conditioned rat

The current report provides a detailed analysis of the changes in the first two components of the auditory evoked potential (AEP) that accompany associative learning. AEPs were recorded from the primary auditory cortex before and after training sessions. Experimental subjects underwent one (n=5) or two (n=7) days of conditioning in which a tone, serving as a conditioned stimulus (CS), was paired with mild foot shock. Control subjects received one (n=5) or two (n=7) days of exposure to the same stimuli delivered randomly. Only animals receiving paired CS-US training developed a conditioned tachycardia response to the tone. Our analyses demonstrated that both early components of the AEP recorded from the granular layer of the cortex undergo CS-specific associative changes: (1) the first, negative component (occurring ∼21ms following tone onset) was significantly augmented after one and two days of training while maintaining its latency, and (2) the second, positive component (occurring ∼50ms following tone onset) was augmented after two days of training, and showed a significant reduction in latency after one and two days of training. We view these changes as evidence of increased cortical synchronization, thereby lending new insight into the temporal dynamics of neural network activity related to auditory learning.

Midbrain dopaminergic neuron activity across alternating brain states of urethane anaesthetized rat

Midbrain dopaminergic neurons are implicated in the control of motor functions and reward-driven behaviours. The function of this neuronal population is strongly connected with distinct patterns of firing - irregular or bursting, which either maintains basal levels of dopamine (DA) or leads to phasic release, respectively. Heterogeneity of dopaminergic neurons, observed on both structural and functional levels, is also reflected in different responses of DA neurons to changes in global brain states. Preparation of urethane anaesthetized animal is a broadly used model to study brain state dependent activity of neurons. Unfortunately activity of midbrain DA neurons across urethane induced cyclic, spontaneous brain state alternations is poorly described. To fulfil this gap in our knowledge we have performed simultaneous, extracellular recordings of the firing of single putative DA neurons combined with continuous brain state monitoring. We found that during slow wave activity, the firing rate of recorded putative DA neurons was significantly higher compared to firing rates during activated state, both in ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). In the presence of cortical slow waves, putative dopaminergic neurons also intensified bursting activity, but the magnitude of this phenomena differed in respect to the examined region (VTA or SNc). Our results show that activity of DA neurons under urethane anaesthesia is brain-state dependent and emphasize the importance of brain state monitoring during electrophysiological experiments.

Anesthesia effect on single local field potentials variability in rat barrel cortex: Preliminary results

The rat barrel cortex is a widely used model of information processing in the somatosensory area, thanks to its precise and easily recognizable organization. However, evoked Local Field Potentials (LFPs) generated in the barrel cortex by repetitive deflections of rat whiskers show large variability in shapes and timings. Moreover, anesthetics can deeply affect the profile of evoked responses. This paper presents preliminary report on the variability and the effect of commonly used anesthetics on these signals. We studied representative signal shape characteristics (e.g., latency and amplitude of events) extracted from evoked responses acquired by means of standard Ag/AgCl electrodes from different cortical layers. As an early result, we found significant difference in the latency of the first principal peak of the responses. Under Tiletamine-Xylazine anesthetic, the responses or events of the evoked LFPs occurred later than the ones recorded while urethane was administered. Furthermore, the distributions of the peak latencies in all cortical layers were narrower in case of Urethane. This behavior should be attributed to the different effects of these two anesthetics on specific synaptic receptors and thus on the processing of neural information and the encoding of sensory input along the cortical pathway.

Autonomous Optimization of Targeted Stimulation of Neuronal Networks

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.

Electrical stimulation of the brain is increasingly used to alleviate the symptoms of a range of neurological disorders and as a means to artificially inject information into neural circuits in neuroprosthetic applications. Machine learning has been proposed to find optimal stimulation settings autonomously. However, this approach is impeded by the complexity of the interaction between the stimulus and the activity of the network, which makes it difficult to test how good the result actually is. We used phenomenological models of the interaction between stimulus and spontaneous activity in a neuronal network to design a testable machine learning challenge and evaluate the quality of the solution found by the algorithm. In this task, the learning algorithm had to find a solution that balances competing interdependencies of ongoing neuronal activity with opposing effects on the efficacy of stimulation. We show that machine learning can successfully solve this task and that the solutions found are close to the optimal settings to maximize the efficacy of stimulation. Since the paradigm involves several typical problems found in other settings, such concepts could help to formalize machine learning problems in more complex biological networks and to test the quality of their performance.

Optimal weighted averaging of event related activity from acquisitions with artifacts

In several biomedical applications that require the signal processing of biological data, the starting procedure for noise reduction is the ensemble averaging of multiple repeated acquisitions (trials). This method is based on the assumption that each trial is composed of two additive components: (i) a time-locked activity related to some sensitive/stimulation phenomenon (ERA, Event Related Activity in the following) and (ii) a sum of several other non time-locked background activities. The averaging aims at estimating the ERA activity under very low Signal to Noise and Interference Ratio (SNIR). Although averaging is a well established tool, its performance can be improved in the presence of high-power disturbances (artifacts) by a trials classification and removal stage. In this paper we propose, model and evaluate a new approach that avoids trials removal, managing trials classified as artifact-free and artifact-prone with two different weights. Based on the model, a weights tuning is possible and through modeling and simulations we show that, when optimally configured, the proposed solution outperforms classical approaches.

A low-cost, multiplexed μECoG system for high-density recordings in freely moving rodents

OBJECTIVE

Micro-electrocorticography (μECoG) offers a minimally invasive neural interface with high spatial resolution over large areas of cortex. However, electrode arrays with many contacts that are individually wired to external recording systems are cumbersome and make recordings in freely behaving rodents challenging. We report a novel high-density 60-electrode system for μECoG recording in freely moving rats.

APPROACH

Multiplexed headstages overcome the problem of wiring complexity by combining signals from many electrodes to a smaller number of connections. We have developed a low-cost, multiplexed recording system with 60 contacts at 406 μm spacing. We characterized the quality of the electrode signals using multiple metrics that tracked spatial variation, evoked-response detectability, and decoding value. Performance of the system was validated both in anesthetized animals and freely moving awake animals.

MAIN RESULTS

We recorded μECoG signals over the primary auditory cortex, measuring responses to acoustic stimuli across all channels. Single-trial responses had high signal-to-noise ratios (SNR) (up to 25 dB under anesthesia), and were used to rapidly measure network topography within ∼10 s by constructing all single-channel receptive fields in parallel. We characterized evoked potential amplitudes and spatial correlations across the array in the anesthetized and awake animals. Recording quality in awake animals was stable for at least 30 days. Finally, we used these responses to accurately decode auditory stimuli on single trials.

SIGNIFICANCE

This study introduces (1) a μECoG recording system based on practical hardware design and (2) a rigorous analytical method for characterizing the signal characteristics of μECoG electrode arrays. This methodology can be applied to evaluate the fidelity and lifetime of any μECoG electrode array. Our μECoG-based recording system is accessible and will be useful for studies of perception and decision-making in rodents, particularly over the entire time course of behavioral training and learning.

Immediate manifestation of acoustic trauma in the auditory cortex is layer specific and cell type dependent

Exposure to loud sounds damages the auditory periphery and induces maladaptive changes in central parts of the auditory system. Diminished peripheral afferentation and altered inhibition influence the processing of sounds in the auditory cortex. It is unclear, however, which types of inhibitory interneurons are affected by acoustic trauma. Here we used single-unit electrophysiological recording and two-photon calcium imaging in anesthetized mice to evaluate the effects of acute acoustic trauma (125 dB SPL, white noise, 5 min) on the response properties of neurons in the core auditory cortex. Electrophysiological measurements suggested the selective impact of acoustic trauma on inhibitory interneurons in the auditory cortex. To further investigate which interneuronal types were affected, we used two-photon calcium imaging to record the activity of neurons in cortical layers 2/3 and 4, specifically focusing on parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons. Spontaneous and pure-tone-evoked firing rates of SST+ interneurons increased in layer 4 immediately after acoustic trauma and remained almost unchanged in layer 2/3. Furthermore, PV+ interneurons with high best frequencies increased their evoked-to-spontaneous firing rate ratios only in layer 2/3 and did not change in layer 4. Finally, acoustic trauma unmasked low-frequency excitatory inputs only in layer 2/3. Our results demonstrate layer-specific changes in the activity of auditory cortical inhibitory interneurons within minutes after acoustic trauma.

Local field potential correlates of auditory working memory in primate dorsal temporal pole

Dorsal temporal pole (dTP) is a cortical region at the rostral end of the superior temporal gyrus that forms part of the ventral auditory object processing pathway. Anatomical connections with frontal and medial temporal areas, as well as a recent single-unit recording study, suggest this area may be an important part of the network underlying auditory working memory (WM). To further elucidate the role of dTP in auditory WM, local field potentials (LFPs) were recorded from the left dTP region of two rhesus macaques during an auditory delayed matching-to-sample (DMS) task. Sample and test sounds were separated by a 5-s retention interval, and a behavioral response was required only if the sounds were identical (match trials). Sensitivity of auditory evoked responses in dTP to behavioral significance and context was further tested by passively presenting the sounds used as auditory WM memoranda both before and after the DMS task. Average evoked potentials (AEPs) for all cue types and phases of the experiment comprised two small-amplitude early onset components (N20, P40), followed by two broad, large-amplitude components occupying the remainder of the stimulus period (N120, P300), after which a final set of components were observed following stimulus offset (N80OFF, P170OFF). During the DMS task, the peak amplitude and/or latency of several of these components depended on whether the sound was presented as the sample or test, and whether the test matched the sample. Significant differences were also observed among the DMS task and passive exposure conditions. Comparing memory-related effects in the LFP signal with those obtained in the spiking data raises the possibility some memory-related activity in dTP may be locally produced and actively generated. The results highlight the involvement of dTP in auditory stimulus identification and recognition and its sensitivity to the behavioral significance of sounds in different contexts. This article is part of a Special Issue entitled SI: Auditory working memory.

Spatial diversity of spontaneous activity in the cortex

The neocortex is a layered sheet across which a basic organization is thought to widely apply. The variety of spontaneous activity patterns is similar throughout the cortex, consistent with the notion of a basic cortical organization. However, the basic organization is only an outline which needs adjustments and additions to account for the structural and functional diversity across cortical layers and areas. Such diversity suggests that spontaneous activity is spatially diverse in any particular behavioral state. Accordingly, this review summarizes the laminar and areal diversity in cortical activity during fixation and slow oscillations, and the effects of attention, anesthesia and plasticity on the cortical distribution of spontaneous activity. Among questions that remain open, characterizing the spatial diversity in spontaneous membrane potential may help elucidate how differences in circuitry among cortical regions supports their varied functions. More work is also needed to understand whether cortical spontaneous activity not only reflects cortical circuitry, but also contributes to determining the outcome of plasticity, so that it is itself a factor shaping the functional diversity of the cortex.

New perspectives on the auditory cortex: learning and memory

Primary ("early") sensory cortices have been viewed as stimulus analyzers devoid of function in learning, memory, and cognition. However, studies combining sensory neurophysiology and learning protocols have revealed that associative learning systematically modifies the encoding of stimulus dimensions in the primary auditory cortex (A1) to accentuate behaviorally important sounds. This "representational plasticity" (RP) is manifest at different levels. The sensitivity and selectivity of signal tones increase near threshold, tuning above threshold shifts toward the frequency of acoustic signals, and their area of representation can increase within the tonotopic map of A1. The magnitude of area gain encodes the level of behavioral stimulus importance and serves as a substrate of memory strength. RP has the same characteristics as behavioral memory: it is associative, specific, develops rapidly, consolidates, and can last indefinitely. Pairing tone with stimulation of the cholinergic nucleus basalis induces RP and implants specific behavioral memory, while directly increasing the representational area of a tone in A1 produces matching behavioral memory. Thus, RP satisfies key criteria for serving as a substrate of auditory memory. The findings suggest a basis for posttraumatic stress disorder in abnormally augmented cortical representations and emphasize the need for a new model of the cerebral cortex.

Suppression and facilitation of auditory neurons through coordinated acoustic and midbrain stimulation: investigating a deep brain stimulator for tinnitus

OBJECTIVE

The inferior colliculus (IC) is the primary processing center of auditory information in the midbrain and is one site of tinnitus-related activity. One potential option for suppressing the tinnitus percept is through deep brain stimulation via the auditory midbrain implant (AMI), which is designed for hearing restoration and is already being implanted in deaf patients who also have tinnitus. However, to assess the feasibility of AMI stimulation for tinnitus treatment we first need to characterize the functional connectivity within the IC. Previous studies have suggested modulatory projections from the dorsal cortex of the IC (ICD) to the central nucleus of the IC (ICC), though the functional properties of these projections need to be determined.

APPROACH

In this study, we investigated the effects of electrical stimulation of the ICD on acoustic-driven activity within the ICC in ketamine-anesthetized guinea pigs.

MAIN RESULTS

We observed ICD stimulation induces both suppressive and facilitatory changes across ICC that can occur immediately during stimulation and remain after stimulation. Additionally, ICD stimulation paired with broadband noise stimulation at a specific delay can induce greater suppressive than facilitatory effects, especially when stimulating in more rostral and medial ICD locations.

SIGNIFICANCE

These findings demonstrate that ICD stimulation can induce specific types of plastic changes in ICC activity, which may be relevant for treating tinnitus. By using the AMI with electrode sites positioned with the ICD and the ICC, the modulatory effects of ICD stimulation can be tested directly in tinnitus patients.

Spiking in auditory cortex following thalamic stimulation is dominated by cortical network activity

The state of the sensory cortical network can have a profound impact on neural responses and perception. In rodent auditory cortex, sensory responses are reported to occur in the context of network events, similar to brief UP states, that produce "packets" of spikes and are associated with synchronized synaptic input (Bathellier et al., 2012; Hromadka et al., 2013; Luczak et al., 2013). However, traditional models based on data from visual and somatosensory cortex predict that ascending sensory thalamocortical (TC) pathways sequentially activate cells in layers 4 (L4), L2/3, and L5. The relationship between these two spatio-temporal activity patterns is unclear. Here, we used calcium imaging and electrophysiological recordings in murine auditory TC brain slices to investigate the laminar response pattern to stimulation of TC afferents. We show that although monosynaptically driven spiking in response to TC afferents occurs, the vast majority of spikes fired following TC stimulation occurs during brief UP states and outside the context of the L4>L2/3>L5 activation sequence. Specifically, monosynaptic subthreshold TC responses with similar latencies were observed throughout layers 2-6, presumably via synapses onto dendritic processes located in L3 and L4. However, monosynaptic spiking was rare, and occurred primarily in L4 and L5 non-pyramidal cells. By contrast, during brief, TC-induced UP states, spiking was dense and occurred primarily in pyramidal cells. These network events always involved infragranular layers, whereas involvement of supragranular layers was variable. During UP states, spike latencies were comparable between infragranular and supragranular cells. These data are consistent with a model in which activation of auditory cortex, especially supragranular layers, depends on internally generated network events that represent a non-linear amplification process, are initiated by infragranular cells and tightly regulated by feed-forward inhibitory cells.

Effects of location and timing of co-activated neurons in the auditory midbrain on cortical activity: implications for a new central auditory prosthesis

OBJECTIVE

An increasing number of deaf individuals are being implanted with central auditory prostheses, but their performance has generally been poorer than for cochlear implant users. The goal of this study is to investigate stimulation strategies for improving hearing performance with a new auditory midbrain implant (AMI). Previous studies have shown that repeated electrical stimulation of a single site in each isofrequency lamina of the central nucleus of the inferior colliculus (ICC) causes strong suppressive effects in elicited responses within the primary auditory cortex (A1). Here we investigate if improved cortical activity can be achieved by co-activating neurons with different timing and locations across an ICC lamina and if this cortical activity varies across A1.

APPROACH

We electrically stimulated two sites at different locations across an isofrequency ICC lamina using varying delays in ketamine-anesthetized guinea pigs. We recorded and analyzed spike activity and local field potentials across different layers and locations of A1.

RESULTS

Co-activating two sites within an isofrequency lamina with short inter-pulse intervals (<5 ms) could elicit cortical activity that is enhanced beyond a linear summation of activity elicited by the individual sites. A significantly greater extent of normalized cortical activity was observed for stimulation of the rostral-lateral region of an ICC lamina compared to the caudal-medial region. We did not identify any location trends across A1, but the most cortical enhancement was observed in supragranular layers, suggesting further integration of the stimuli through the cortical layers.

SIGNIFICANCE

The topographic organization identified by this study provides further evidence for the presence of functional zones across an ICC lamina with locations consistent with those identified by previous studies. Clinically, these results suggest that co-activating different neural populations in the rostral-lateral ICC rather than the caudal-medial ICC using the AMI may improve or elicit different types of hearing capabilities.

Synaptic dynamics contribute to long-term single neuron response fluctuations

Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of the ensemble of synapses–activated in response to a given stimulus–on single neuron response variability. We present and validate a method tailored for controlled and specific long-term activation of a single cortical neuron in vitro via synaptic or antidromic stimulation, enabling a clear separation between two determinants of neuronal response variability: membrane excitability dynamics vs. synaptic dynamics. Applying this method we show that, within the range of physiological activation frequencies, the synaptic ensemble of a given neuron is a key contributor to the neuronal response variability, long-memory processes and complex statistics observed over extended time scales. Synaptic transmission dynamics impact on response variability in stimulation rates that are substantially lower compared to stimulation rates that drive excitability resources to fluctuate. Implications to network embedded neurons are discussed.

Spontaneous slow oscillations and sequential patterns due to short-term plasticity in a model of the cortex

We study a realistic model of a cortical column taking into account short-term plasticity between pyramidal cells and interneurons. The simulation of leaky integrate-and-fire neurons shows that low-frequency oscillations emerge spontaneously as a result of intrinsic network properties. These oscillations are composed of prolonged phases of high and low activity reminiscent of cortical up and down states, respectively. We simplify the description of the network activity by using a mean field approximation and reduce the system to two slow variables exhibiting some relaxation oscillations. We identify two types of slow oscillations. When the combination of dynamic synapses between pyramidal cells and those between interneurons accounts for the generation of these slow oscillations, the end of the up phase is characterized by asynchronous fluctuations of the membrane potentials. When the slow oscillations are mainly driven by the dynamic synapses between interneurons, the network exhibits fluctuations of membrane potentials, which are more synchronous at the end than at the beginning of the up phase. Additionally, finite size effect and slow synaptic currents can modify the irregularity and frequency, respectively, of these oscillations. Finally, we consider possible roles of a slow oscillatory input modeling long-range interactions in the brain. Spontaneous slow oscillations of local networks are modulated by the oscillatory input, which induces, notably, synchronization, subharmonic synchronization, and chaotic relaxation oscillations in the mean field approximation. In the case of forced oscillations, the slow population-averaged activity of leaky integrate-and-fire neurons can have both deterministic and stochastic temporal features. We discuss the possibility that long-range connectivity controls the emergence of slow sequential patterns in local populations due to the tendency of a cortical column to oscillate at low frequency.