Single Unit publications

General anesthesia is ubiquitous in research and medicine, yet although the molecular mechanisms of anesthetics are well characterized, their ultimate influence on cortical electrophysiology remains unclear. Moreover, the influence that different anesthetics have on sensory cortexes at neuronal and ensemble scales is mostly unknown and represents an important gap in knowledge that has widespread relevance for neural sciences. To address this knowledge gap, this work explored the effects of isoflurane and ketamine/xylazine, two widely used anesthetic paradigms, on electrophysiological behavior in mouse primary visual cortex. First, multiunit activity and local field potentials were examined to understand how each anesthetic influences spontaneous activity. Then, the interlaminar relationships between populations of neurons at different cortical depths were studied to assess whether anesthetics influenced resting-state functional connectivity. Lastly, the spatiotemporal dynamics of visually evoked multiunit and local field potentials were examined to determine how each anesthetic alters communication of visual information. We found that isoflurane enhanced the rhythmicity of spontaneous ensemble activity at 10–40 Hz, which coincided with large increases in coherence between layer IV with superficial and deep layers. Ketamine preferentially increased local field potential power from 2 to 4 Hz, and the largest increases in coherence were observed between superficial and deep layers. Visually evoked responses across layers were diminished under isoflurane, and enhanced under ketamine anesthesia. These findings demonstrate that isoflurane and ketamine anesthesia differentially impact sensory processing in V1. NEW & NOTEWORTHY We directly compared electrophysiological responses in awake and anesthetized (isoflurane or ketamine) mice. We also proposed a method for quantifying and visualizing highly variable, evoked multiunit activity. Lastly, we observed distinct oscillatory responses to stimulus onset and offset in awake and isoflurane-anesthetized mice.

In mouse models of Fragile X Syndrome (FXS), cellular and circuit hyperexcitability are a consequence of altered brain development [reviewed in (Contractor et al., 2015)]. Mechanisms that favor or hinder plasticity of synapses could affect neuronal excitability. This includes inhibitory long term depression (I-LTD) – a heterosynaptic form of plasticity that requires the activation of metabotropic glutamate receptors (mGluRs). Differential circuit maturation leads to shifted time points for critical periods of synaptic plasticity across multiple brain regions (Harlow et al., 2010; He et al., 2014), and disruptions of the development of excitatory and inhibitory synaptic function are also observed both during development and into adulthood (Vislay et al., 2013). However, little is known about how this hyperexcitable environment affects inhibitory synaptic plasticity. Our results demonstrate that the somatosensory cortex of the Fmr1 KO mouse model of FXS exhibits increased GABAergic spontaneous activity, a faulty mGluR-mediated inhibitory input and impaired plasticity processes. We find the overall diminished mGluR activation in the Fmr1 KO mice leads to both a decreased spontaneous inhibitory postsynaptic input to principal cells and also to a disrupted form of inhibitory long term depression (I-LTD). In cortical synapses, this I-LTD is dependent on mGluR activation and the mobilization endocannabinoids (eCBs). Notably, these data suggest enhanced hyperexcitable phenotypes in FXS may be homeostatically counterbalanced by the inhibitory drive of the network and its altered response to mGluR modulation. Significance Statement Fragile X Syndrome is a pervasive neurodevelopmental disorder characterized by intellectual disability, autism, epilepsy, anxiety and altered sensory sensitivity. In both in vitro and in vivo recordings in the somatosensory cortex of the Fmr1 knockout mouse model of Fragile X Syndrome we show that hyperexcitable network activity contributes to ineffective synaptic plasticity at inhibitory synapses. This increased excitability prevents cortical circuits from adapting to sensory information via ineffective plasticity mechanisms.

Oscillations in the brain facilitate neural processing and cognitive functions. This study investigated the dependence of long-term potentiation (LTP), a neural correlate of memory, on the phase of the hippocampal θ rhythm, a prominent brain oscillation. Multichannel field potentials and current source-sinks were analyzed in hippocampal CA1 of adult male rats under urethane anesthesia. A single burst (five pulses at 200 Hz) stimulation of stratum oriens (OR) induced LTP of the basal dendritic excitatory sink (ES), which was maximal when the burst was delivered at ∼340° and ∼160° of the distal dendritic θ rhythm. Apical dendritic sink evoked by stratum radiatum (RAD) stimulation also showed biphasic maxima at ∼30° and ∼210° of the distal dendritic θ rhythm, about 50° phase delay to basal dendritic LTP. By contrast, maximal population spike (PS) excitability, following single-pulse excitation of the basal or mid-apical dendrites, occurred at a θ phase of ∼140°, and maximal basal dendritic ES occurred at ∼20°; γ (30–57 Hz) activity recorded in CA1 RAD had maximal power at ∼300° of the distal dendritic θ rhythm, different from the phases of maximal LTP. LTP induced during the rising θ phase was NMDA receptor sensitive. It is suggested that the θ phase modulation of CA1 PS excitability is mainly provided by θ-rhythmic proximal inhibition, while dendritic LTP is also modulated by dendritic inhibition and excitation, specific to basal and apical dendrites. In summary, basal and apical dendritic synaptic plasticity and spike excitability are facilitated at different θ phases in a compartmental fashion.

Dopamine modulates medial prefrontal cortex (mPFC) activity to mediate diverse behavioural functions1,2; however, the precise circuit computations remain unknown. One potentially unifying model by which dopamine may underlie a diversity of functions is by modulating the signal-to-noise ratio in subpopulations of mPFC neurons3-6, where neural activity conveying sensory information (signal) is amplified relative to spontaneous firing (noise). Here we demonstrate that dopamine increases the signal-to-noise ratio of responses to aversive stimuli in mPFC neurons projecting to the dorsal periaqueductal grey (dPAG). Using an electrochemical approach, we reveal the precise time course of pinch-evoked dopamine release in the mPFC, and show that mPFC dopamine biases behavioural responses to aversive stimuli. Activation of mPFC-dPAG neurons is sufficient to drive place avoidance and defensive behaviours. mPFC-dPAG neurons display robust shock-induced excitations, as visualized by single-cell, projection-defined microendoscopic calcium imaging. Finally, photostimulation of dopamine terminals in the mPFC reveals an increase in the signal-to-noise ratio in mPFC-dPAG responses to aversive stimuli. Together, these data highlight how dopamine in the mPFC can selectively route sensory information to specific downstream circuits, representing a potential circuit mechanism for valence processing.

Frequency tuning and phase-locking are two fundamental properties generated in the cochlea, enabling but also limiting the coding of sounds by the auditory nerve (AN). In humans, these limits are unknown, but high resolution has been postulated for both properties. Electrophysiological recordings from the AN of normal-hearing volunteers indicate that human frequency tuning, but not phase-locking, exceeds the resolution observed in animal models.

Growing evidence suggests that sensory neurons achieve optimal encoding by matching their tuning properties to the natural stimulus statistics. However, the underlying mechanisms remain unclear. Here we demonstrate that feedback pathways from higher brain areas mediate optimized encoding of naturalistic stimuli via temporal whitening in the weakly electric fish Apteronotus leptorhynchus. While one source of direct feedback uniformly enhances neural responses, a separate source of indirect feedback selectively attenuates responses to low frequencies, thus creating a high-pass neural tuning curve that opposes the decaying spectral power of natural stimuli. Additionally, we recorded from two populations of higher brain neurons responsible for the direct and indirect descending inputs. While one population displayed broadband tuning, the other displayed high-pass tuning and thus performed temporal whitening. Hence, our results demonstrate a novel function for descending input in optimizing neural responses to sensory input through temporal whitening that is likely to be conserved across systems and species.

Auditory perception depends on multi-dimensional information in acoustic signals that must be encoded by auditory nerve fibers (ANF). These dimensions are represented by filters with different frequency selectivities. Multiple models have been suggested; however, the identification of relevant filters and type of interactions has been elusive, limiting progress in modeling the cochlear output. Spike-triggered covariance analysis of barn owl ANF responses was used to determine the number of relevant stimulus filters and estimate the nonlinearity that produces responses from filter outputs. This confirmed that ANF responses depend on multiple filters. The first, most dominant filter was the spike-triggered average, which was excitatory for all neurons. The second and third filters could be either suppressive or excitatory with center frequencies above or below that of the first filter. The nonlinear function mapping the first two filter outputs to the spiking probability ranged from restricted to nearly circular-symmetric, reflecting different modes of interaction between stimulus dimensions across the sample. This shows that stimulus encoding in ANFs of the barn owl is multidimensional and exhibits diversity over the population, suggesting that models must allow for variable numbers of filters and types of interactions between filters to describe how sound is encoded in ANFs.

The ability to select the most salient among competing stimuli is essential for animal behavior and operates no matter which spatial locations stimuli happen to occupy. We provide evidence that the brain employs a combinatorially optimized inhibition strategy for selection across all pairs of stimulus locations. With experiments in a key inhibitory nucleus in the vertebrate midbrain selection network, called isthmi pars magnocellularis (Imc) in owls, we discovered that Imc neurons encode visual space with receptive fields that have multiple excitatory hot spots ("lobes"). Such multilobed encoding is necessitated by scarcity of Imc neurons. Although distributed seemingly randomly, the locations of these lobes are optimized across the high-firing Imc neurons, allowing them to combinatorially solve selection across space. This strategy minimizes metabolic and wiring costs, a principle that also accounts for observed asymmetries between azimuthal and elevational coding. Combinatorially optimized inhibition may be a general neural principle for efficient stimulus selection.

The chronic performance of implantable neural electrodes is hindered by inflammatory brain tissue responses, including microglia activation, glial scarring, and neuronal loss. Melatonin (MT) has shown remarkable neuroprotective and neurorestorative effects in treating central nervous system (CNS) injuries and degeneration by inhibiting caspase-1, -3, and -9 activation and mitochondrial cytochrome c release, as well as reducing oxidative stress and neuroinflammation. This study examined the effect of MT administration on the quality and longevity of neural recording from an implanted microelectrode in the visual cortex of mice for 16 weeks. MT (30 mg/kg) was administered via daily intraperitoneal injection for acute (3 days before and 14 days post-implantation) and chronic (3 days before and 16 weeks post-implantation) exposures. During the first 4 weeks, both MT groups showed significantly higher single-unit (SU) yield, signal-to-noise ratio (SNR), and amplitude compared to the vehicle control group. However, after 4 weeks of implantation, the SU yield of the acute treatment group dropped to the same level as the control group, while the chronic treatment group maintained significantly higher SU yield compared to both acute (week 5-16) and control (week 0-16) mice. Histological studies revealed a significant increase in neuronal viability and decrease in neuronal apoptosis around the implanted electrode at week 16 in the chronic group in comparison to control and acute subjects, which is correlated with reduced oxidative stress and increased number of pro-regeneration arginase-1 positive microglia cells. These results demonstrate the potent effect of MT treatment in maintaining a high-quality electrode-tissue interface and suggest that MT promotes neuroprotection possibly through its anti-apoptotic, anti-inflammatory, and anti-oxidative properties.

The largest targets of retinal input in mammals are the dorsal lateral geniculate nucleus (dLGN), a relay to the primary visual cortex (V1), and the superior colliculus. V1 innervates and influences the superior colliculus. Here, we find that, in turn, superior colliculus modulates responses in mouse V1. Optogenetically inhibiting the superior colliculus reduces responses in V1 to optimally sized stimuli. Superior colliculus could influence V1 via its strong projection to the lateral posterior nucleus (LP/Pulvinar) or its weaker projection to the dLGN. Inhibiting superior colliculus strongly reduces activity in LP. Pharmacologically silencing LP itself, however, does not remove collicular modulation of V1. The modulation is instead due to a collicular gain modulation of the dLGN. Surround suppression operating in V1 explains the different effects for differently sized stimuli. Computations of visual saliency in the superior colliculus can thus influence tuning in the visual cortex via a tectogeniculate pathway.

Active mechanical amplification of sound occurs in cochlear outer hair cells (OHCs) that change their length with oscillations of their membrane potential. Such length changes are the proposed cellular source of the cochlear amplifier, and prestin is the motor protein responsible for OHC electromotility. Previous findings have shown that mice lacking prestin displayed a loss of OHC electromotility, subsequent loss of distortion-product otoacoustic emissions, and a 40-60 dB increase in hearing thresholds. In this study we were interested in studying the functional consequences of the complete loss of cochlear amplification on neural coding of frequency selectivity, tuning, and temporal processing in the auditory midbrain. We recorded near-field auditory evoked potentials and multi-unit activity from the inferior colliculus (IC) of prestin (-/-) null and prestin (+/+) wild-type control mice and determined frequency response areas (FRAs), tuning sharpness, and gap detection to tone bursts and silent gaps embedded in broadband noise. We were interested in determining if the moderate to severe sensorineural hearing loss associated with the loss of motor protein prestin would also impair auditory midbrain temporal-processing measures, or if compensatory mechanisms within the brainstem could compensate for the loss of prestin. In prestin knockout mice we observed that there are severe impairments in midbrain tuning, thresholds, excitatory drive, and gap detection suggesting that brainstem and midbrain processing could not overcome the auditory processing deficits afforded by the loss of OHC electromotility mediated by the prestin protein.

Neural recording systems that interface with implanted microelectrodes are used extensively in experimental neuroscience and neural engineering research. Interface electronics that are needed to amplify, filter, and digitize signals from multichannel electrode arrays are a critical bottleneck to scaling such systems. This paper presents the design and testing of an electronic architecture for intracortical neural recording that drastically reduces the size per channel by rapidly multiplexing many electrodes to a single circuit. The architecture utilizes mixed-signal feedback to cancel electrode offsets, windowed integration sampling to reduce aliased high-frequency noise, and a successive approximation analog-to-digital converter with small capacitance and asynchronous control. Results are presented from a 180 nm CMOS integrated circuit prototype verified using in vivo experiments with a tungsten microwire array implanted in rodent cortex. The integrated circuit prototype achieves <0.004 mm2 area per channel, 7 µW power dissipation per channel, 5.6 µVrms input referred noise, 50 dB common mode rejection ratio, and generates 9-bit samples at 30 kHz per channel by multiplexing at 600 kHz. General considerations are discussed for rapid time domain multiplexing of high-impedance microelectrodes. Overall, this work describes a promising path forward for scaling neural recording systems to numbers of electrodes that are orders of magnitude larger.

Auditory streaming is the process by which environmental sound is segregated into discrete perceptual objects. The auditory system has a remarkable capability in this regard as revealed in psychophysical experiments in humans and other primates. However, little is known about the underlying neuronal mechanisms, in part because of the lack of suitable behavioural paradigms in non-primate species. The mouse is an increasingly popular model for studying the neural mechanisms of perception and action because of the range of molecular tools enabling precise manipulation of neural circuitry. Here we present a novel behavioural task that can be used to assess perceptual aspects of auditory streaming in head-fixed mice. Animals were trained to detect a target sound in a one of two simultaneously presented, isochronous pure tone sequences. Temporal expectation was manipulated by presenting the target sound in a particular stream either early (~2 s) or late (~4 s) with respect to trial onset in blocks of 25-30 trials. Animals reached high performance on this task (d' > 1 overall), and notably their false alarms were very instructive of their behavioural state. Indeed, false alarm timing was markedly delayed for late blocks compared to early ones, indicating that the animals associated a different context to an otherwise identical stimulus. More finely, we observed that the false alarms were timed to the onset of the sounds present in the target stream. This suggests that the animals could selectively follow the target stream despite the presence of a distractor stream. Extracellular electrophysiological recordings during the task revealed that sound processing is flexibly modulated in a manner consistent with the optimisation of behavioural outcome. Together, these results indicate that the perceptual streaming can be inferred via the timing of false alarms in mice, and provide a new paradigm with which to investigate neuronal mechanisms of selective attention.

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.

Human orbitofrontal cortex (OFC) has long been implicated in value-based decision making. In recent years, convergent evidence from human and model organisms has further elucidated its role in representing reward-related computations underlying decision making. However, a detailed description of these processes remains elusive due in part to (1) limitations in our ability to observe human OFC neural dynamics at the timescale of decision processes and (2) methodological and interspecies differences that make it challenging to connect human and animal findings or to resolve discrepancies when they arise. Here, we sought to address these challenges by conducting multi-electrode electrocorticography (ECoG) recordings in neurosurgical patients during economic decision making to elucidate the electrophysiological signature, sub-second temporal profile, and anatomical distribution of reward-related computations within human OFC. We found that high-frequency activity (HFA) (70-200 Hz) reflected multiple valuation components grouped in two classes of valuation signals that were dissociable in temporal profile and information content: (1) fast, transient responses reflecting signals associated with choice and outcome processing, including anticipated risk and outcome regret, and (2) sustained responses explicitly encoding what happened in the immediately preceding trial. Anatomically, these responses were widely distributed in partially overlapping networks, including regions in the central OFC (Brodmann areas 11 and 13), which have been consistently implicated in reward processing in animal single-unit studies. Together, these results integrate insights drawn from human and animal studies and provide evidence for a role of human OFC in representing multiple reward computations.

Sounds can arise from the environment and also predictably from many of our own movements, such as vocalizing, walking, or playing music. The capacity to anticipate these movement-related (reafferent) sounds and distinguish them from environmental sounds is essential for normal hearing1,2, but the neural circuits that learn to anticipate the often arbitrary and changeable sounds that result from our movements remain largely unknown. Here we developed an acoustic virtual reality (aVR) system in which a mouse learned to associate a novel sound with its locomotor movements, allowing us to identify the neural circuit mechanisms that learn to suppress reafferent sounds and to probe the behavioural consequences of this predictable sensorimotor experience. We found that aVR experience gradually and selectively suppressed auditory cortical responses to the reafferent frequency, in part by strengthening motor cortical activation of auditory cortical inhibitory neurons that respond to the reafferent tone. This plasticity is behaviourally adaptive, as aVR-experienced mice showed an enhanced ability to detect non-reafferent tones during movement. Together, these findings describe a dynamic sensory filter that involves motor cortical inputs to the auditory cortex that can be shaped by experience to selectively suppress the predictable acoustic consequences of movement.

Frontal eye field (FEF) in macaque monkeys contributes to visual attention, visual-motor transformations and production of eye movements. Traditionally, neurons in FEF have been classified by the magnitude of increased discharge rates following visual stimulus presentation, during a waiting period, and associated with eye movement production. However, considerable heterogeneity remains within the traditional visual, visuomovement, and movement categories. Cluster analysis is a data-driven method of identifying self-segregating groups within a dataset. Because many cluster analysis techniques exist and outcomes vary with analysis assumptions, consensus clustering aggregates over multiple analyses, identifying robust groups. To describe more comprehensively the neuronal composition of FEF, we applied a consensus clustering technique for unsupervised categorization of patterns of spike rate modulation measured during a memory-guided saccade task. We report 10 functional categories, expanding on the traditional 3 categories. Categories were distinguished by latency, magnitude, and sign of visual response; the presence of sustained activity; and the dynamics, magnitude and sign of saccade-related modulation. Consensus clustering can include other metrics and can be applied to datasets from other brain regions to provide better information guiding microcircuit models of cortical function.

Auditory nerve single-unit recordings were obtained from two groups of young barn owls (age, between posthatching days 11 and 86) in terminal experiments under two different anesthetic regimes: ketamine (6-11 mg/kg) plus xylazine (∼2 mg/kg); or isoflurane (1-1.5%) in oxygen, delivered via artificial respiration. In a second series of minimally invasive experiments, auditory brainstem responses (ABRs) were recorded in the same four adult barn owls (Tyto alba; age, between 5 and 32 months) under three different anesthetic protocols: ketamine (10 mg/kg) plus xylazine (3 mg/kg), isoflurane (1-1.5%), and sevoflurane (2-3%) in carbogen. Finally, the ABR measurements on adult owls were repeated in terminal experiments including more invasive procedures such as artificial respiration and higher isoflurane dosage. The main finding was a significant deterioration of auditory sensitivity in barn owls under gas anesthesia, at the level of the auditory nerve (i.e., a very peripheral level of the auditory system). The effect was drastic in the young animals that experienced threshold elevations in auditory nerve single-unit responses of ≥20 dB. ABR thresholds assessed repeatedly in experiments on adult owls were also significantly higher under isoflurane and sevoflurane, on average by 7 and 15 dB, compared with ketamine/xylazine. This difference already occurred with minimal dosages and was reversibly enlarged with increased isoflurane concentration. Finally, there was evidence for confounding detrimental effects associated with artificial respiration over many hours, which suggested oxygen toxicity.

Pairing vagus nerve stimulation (VNS) with movements or sounds can direct robust plasticity in motor or auditory cortex, respectively. The degree of map plasticity is influenced by the intensity and pulse width of VNS, number of VNS-event pairings, and the interval between each pairing. It is likely that these parameters interact, influencing optimal implementation of VNS pairing protocols. We varied VNS intensity, number of stimulations, and inter-stimulation interval (ISI) to test for interactions among these parameters. Rats were implanted with a vagus nerve stimulating cuff and randomly assigned to one of three treatment groups to receive 20 days of VNS paired with a 9-kHz tone: (1) Fast VNS: 50 daily pairings of 400-µA VNS with a 30-s ISI; (2) Dispersed VNS: 50 daily pairings of 400-µA VNS with a 180-s ISI; and (3) Standard VNS: 300 daily pairings of 800-µA VNS with a 30-s ISI. Following 20 days of VNS-tone pairing, multi-unit recordings were conducted in primary auditory cortex (A1) and receptive field properties were analyzed. Increasing ISI (Dispersed VNS) did not lead to an enhancement of cortical plasticity. Reducing the current intensity and number of stimulations (Fast VNS) resulted in robust cortical plasticity, using 6 times fewer VNS pairings than the Standard protocol. These findings reveal an interaction between current intensity, stimulation number, and ISI and identify a novel VNS paradigm that is substantially more efficient than the previous standard paradigm.

Current neuroprosthetics rely on stable, high quality recordings from chronically implanted microelectrode arrays (MEAs) in neural tissue. While chronic electrophysiological recordings and electrode failure modes have been reported from rodent and larger non-human primate (NHP) models, chronic recordings from the marmoset model have not been previously described. The common marmoset is a New World primate that is easier to breed and handle compared to larger NHPs and has a similarly organized brain, making it a potentially useful smaller NHP model for neuroscience studies. This study reports recording stability and signal quality of MEAs chronically implanted in behaving marmosets. Six adult male marmosets, trained for reaching tasks, were implanted with either a 16-channel tungsten microwire array (five animals) or a Pt-Ir floating MEA (one animal) in the hand-arm region of the primary motor cortex (M1) and another MEA in the striatum targeting the nucleus accumbens (NAcc). Signal stability and quality was quantified as a function of array yield (active electrodes that recorded action potentials), neuronal yield (isolated single units during a recording session), and signal-to-noise ratio (SNR). Out of 11 implanted MEAs, nine provided functional recordings for at least three months, with two arrays functional for 10 months. In general, implants had high yield, which remained stable for up to several months. However, mechanical failure attributed to MEA connector was the most common failure mode. In the longest implants, signal degradation occurred, which was characterized by gradual decline in array yield, reduced number of isolated single units, and changes in waveform shape of action potentials. This work demonstrates the feasibility of long-term recordings from MEAs implanted in cortical and deep brain structures in the marmoset model. The ability to chronically record cortical signals for neural prosthetics applications in the common marmoset extends the potential of this model in neural interface research.