Single Unit publications

Proprioceptive feedback is a critical component of voluntary movement planning and execution. Neuroprosthetic technologies aiming at restoring movement must interact with it to restore accurate motor control. Optimization and design of such technologies depends on the availability of quantitative insights into the neural dynamics of proprioceptive afferents during functional movements. However, recording proprioceptive neural activity during unconstrained movements in clinically relevant animal models presents formidable challenges. In this work, we developed a computational framework to estimate the spatiotemporal patterns of proprioceptive inputs to the cervical spinal cord during three-dimensional arm movements in monkeys. We extended a biomechanical model of the monkey arm with ex-vivo measurements, and combined it with models of mammalian group-Ia, Ib and II afferent fibers. We then used experimental recordings of arm kinematics and muscle activity of two monkeys performing a reaching and grasping task to estimate muscle stretches and forces with computational biomechanics. Finally, we projected the simulated proprioceptive firing rates onto the cervical spinal roots, thus obtaining spatiotemporal maps of spinal proprioceptive inputs during voluntary movements. Estimated maps show complex and markedly distinct patterns of neural activity for each of the fiber populations spanning the spinal cord rostro-caudally. Our results indicate that reproducing the proprioceptive information flow to the cervical spinal cord requires complex spatio-temporal modulation of each spinal root. Our model can support the design of neuroprosthetic technologies as well as in-silico investigations of the primate sensorimotor system.

Somatostatin improves visual perception by reducing excitatory inputs to the parvalbumin-positive interneurons in the cortex.

Sensory information–driven spikes are synchronized across cortical layers by distinct subtypes of interneurons.

Do noises wake you up at night? Blame your locus coeruleus.

We investigated whether contrast gain control is mediated by shunting inhibition from parvalbumin-positive interneurons in auditory cortex. We performed extracellular and intracellular recordings in mouse auditory cortex while presenting sensory stimuli with varying contrasts and manipulated parvalbumin-positive interneuron activity using optogenetics. We show that while parvalbumin-positive interneuron activity modulates the gain of cortical responses, this activity is not the primary mechanism for contrast gain control in auditory cortex.

Accumulation of amyloid β oligomers (AβO) in Alzheimer’s disease (AD) impairs hippocampal theta and gamma oscillations. These oscillations are important in memory functions and depend on distinct subtypes of hippocampal interneurons such as somatostatin-positive (SST) and parvalbumin-positive (PV) interneurons. Here, we investigated whether AβO causes dysfunctions in SST and PV interneurons by optogenetically manipulating them during theta and gamma oscillations in vivo in AβO-injected SST-Cre or PV-Cre mice. Hippocampal in vivo multi-electrode recordings revealed that optogenetic activation of channelrhodopsin-2 (ChR2)-expressing SST and PV interneurons in AβO-injected mice selectively restored AβO-induced reduction of the peak power of theta and gamma oscillations, respectively, and resynchronized CA1 pyramidal cell (PC) spikes. Moreover, SST and PV interneuron spike phases were resynchronized relative to theta and gamma oscillations, respectively. Whole-cell voltage-clamp recordings in CA1 PC in ex vivo hippocampal slices from AβO-injected mice revealed that optogenetic activation of SST and PV interneurons enhanced spontaneous inhibitory postsynaptic currents (IPSCs) selectively at theta and gamma frequencies, respectively. Furthermore, analyses of the stimulus–response curve, paired-pulse ratio, and short-term plasticity of SST and PV interneuron-evoked IPSCs ex vivo showed that AβO increased the initial GABA release probability to depress SST/PV interneuron’s inhibitory input to CA1 PC selectively at theta and gamma frequencies, respectively. Our results reveal frequency-specific and interneuron subtype-specific presynaptic dysfunctions of SST and PV interneurons’ input to CA1 PC as the synaptic mechanisms underlying AβO-induced impairments of hippocampal network oscillations and identify them as potential therapeutic targets for restoring hippocampal network oscillations in early AD.

Key points We measured fractal (self‐similar) fluctuations in ongoing spiking activity in subcortical (lateral geniculate nucleus, LGN) and cortical (area MT) visual areas in anaesthetised marmosets. Cells in the evolutionary ancient koniocellular LGN pathway and in area MT show high‐amplitude fractal fluctuations, whereas evolutionarily newer parvocellular and magnocellular LGN cells do not. Spiking activity in koniocellular cells and MT cells shows substantial correlation to the local population activity, whereas activity in parvocellular and magnocellular cells is less correlated with local activity. We develop a model consisting of a fractal process and a global rate modulation which can reproduce and explain the fundamental relationship between fractal fluctuations and population coupling in LGN and MT. The model provides a unified account of apparently disparate aspects of neural spiking activity and can improve our understanding of information processing in evolutionary ancient and modern visual pathways. Abstract The brain represents and processes information through patterns of spiking activity, which is influenced by local and widescale brain circuits as well as intrinsic neural dynamics. Whether these influences have independent or linked effects on spiking activity is, however, not known. Here we measured spiking activity in two visual centres, the lateral geniculate nucleus (LGN) and cortical area MT, in marmoset monkeys. By combining the Fano‐factor time curve, power spectral analysis and rescaled range analysis, we reveal inherent fractal fluctuations of spiking activity in LGN and MT. We found that the evolutionary ancient koniocellular (K) pathway in LGN and area MT exhibits strong fractal fluctuations at short (<1 s) time scales. Parvocellular (P) and magnocellular (M) LGN cells show weaker fractal fluctuations at longer (multi‐second) time scales. In both LGN and MT, the amplitude and time scale of fractal fluctuations can explain short and long time scale spiking dynamics. We further show differential neuronal coupling of LGN and MT cells to local population spiking activity. The population coupling is intrinsically linked to fractal fluctuations: neurons showing stronger fluctuations are more strongly correlated to the local population activity. To understand this relationship, we modelled spiking activity using a fractal inhomogeneous Poisson process with dynamic rate, which is the product of an intrinsic stochastic fractal rate and a global modulatory gain. Our model explains the intrinsic links between neuronal spike rate and population coupling in LGN and MT, and establishes a unified account of dynamic spiking properties in afferent visual pathways.

Neural adaptation enables sensory information to be represented optimally in the brain despite large fluctuations over time in the statistics of the environment. Auditory contrast gain control represents an important example, which is thought to arise primarily from cortical processing. Here we show that neurons in the auditory thalamus and midbrain of mice show robust contrast gain control, and that this is implemented independently of cortical activity. Although neurons at each level exhibit contrast gain control to similar degrees, adaptation time constants become longer at later stages of the processing hierarchy, resulting in progressively more stable representations. We also show that auditory discrimination thresholds in human listeners compensate for changes in contrast, and that the strength of this perceptual adaptation can be predicted from physiological measurements. Contrast adaptation is therefore a robust property of both the subcortical and cortical auditory system and accounts for the short-term adaptability of perceptual judgments.

The ability to recognize sounds in noise is a key part of hearing, and the mechanisms by which the brain identifies sounds in noise are of considerable interest to scientists, clinicians and engineers. Yet we know little about the necessity of regions such as auditory cortex for hearing in noise, or how cortical processing of sounds is adversely affected by noise. Here we used reversible cortical inactivation and extracellular electrophysiology in ferrets performing a vowel discrimination task to identify and understand the causal contribution of auditory cortex to hearing in noise. Cortical inactivation by cooling impaired task performance in noisy but not clean conditions, while responses of auditory cortical neurons were less informative about vowel identity in noise. Simulations mimicking cortical inactivation indicated that effects of inactivation were related to the loss of information about sounds represented across neural populations. The addition of noise to target sounds drove spiking activity in auditory cortex and recruitment of additional neural populations that were linked to degraded behavioral performance. To suppress noise-related activity, we used continuous exposure to background noise to adapt the auditory system and recover behavioral performance in both ferrets and humans. Inactivation by cooling revealed that the benefits of continuous exposure were not cortically dependent. Together our results highlight the importance of auditory cortex in sound discrimination in noise and the underlying mechanisms through which noise-related activity and adaptation shape hearing.

Manipulations that enhance neuroplasticity may inadvertently create opportunities for maladaptation. We have previously used passive exposures to non-traumatic white noise to open windows of plasticity in the adult rat auditory cortex and induce frequency-specific functional reorganizations of the tonotopic map. However, similar reorganizations in the central auditory pathway are thought to contribute to the generation of hearing disorders such as tinnitus and hyperacusis. Here, we investigate whether noise-induced reorganizations are accompanied by electrophysiological or behavioral evidence of tinnitus or hyperacusis in adult Long-Evans rats. We used a 2-week passive exposure to moderate-intensity (70 dB SPL) broadband white noise to reopen a critical period for spectral tuning such that a second 1-week exposure to 7 kHz tone pips produced an expansion of the 7 kHz frequency region in the primary auditory cortex (A1). We demonstrate for the first time that this expansion also takes place in the ventral auditory field (VAF). Sound exposure also led to spontaneous and sound-evoked hyperactivity in the anterior auditory field (AAF). Rats were assessed for behavioral evidence of tinnitus or hyperacusis using gap and tone prepulse inhibition of the acoustic startle response. We found that sound exposure did not affect gap-prepulse inhibition. However, sound exposure led to an improvement in prepulse inhibition when the prepulse was a 7 kHz tone, showing that exposed rats had enhanced sensorimotor gating for the exposure frequency. Together, our electrophysiological and behavioral results provide evidence of hyperacusis but not tinnitus in sound-exposed animals. Our findings demonstrate that periods of prolonged noise exposure may open windows of plasticity that can also be understood as windows of vulnerability, potentially increasing the likelihood for maladaptive plasticity to take place.

The gaseous free radical, nitric oxide ( NO ) acts as a ubiquitous neuromodulator, contributing to synaptic plasticity in a complex way that can involve either long term potentiation or depression. It is produced by neuronal nitric oxide synthase ( nNOS ) which is presynaptically expressed and also located postsynaptically in the membrane and cytoplasm of a subpopulation of each major neuronal type in the ventral cochlear nucleus ( VCN ). We have used iontophoresis in vivo to study the effect of the NOS inhibitor L‐ NAME (L‐ NG ‐Nitroarginine methyl ester) and the NO donors SIN ‐1 (3‐Morpholinosydnonimine hydrochloride) and SNOG (S‐Nitrosoglutathione) on VCN units under urethane anaesthesia. Collectively, both donors produced increases and decreases in driven and spontaneous firing rates of some neurones. Inhibition of endogenous NO production with L‐ NAME evoked a consistent increase in driven firing rates in 18% of units without much effect on spontaneous rate. This reduction of gain produced by endogenous NO was mirrored when studying the effect of L‐ NAME on NMDA ( N ‐Methyl‐D‐aspartic acid)‐evoked excitation, with 30% of units showing enhanced NMDA ‐evoked excitation during L‐ NAME application (reduced NO levels). Approximately 25% of neurones contain nNOS and the NO produced can modulate the firing rate of the main principal cells: medium stellates (choppers), large stellates (onset responses) and bushy cells (primary‐like responses). The main endogenous role of NO seems to be to partly suppress driven firing rates associated with NMDA channel activity but there is scope for it to increase neural gain if there were a pathological increase in its production following hearing loss.

Humans and other animals effortlessly identify natural sounds and categorize them into behaviorally relevant categories. Yet, the acoustic features and neural transformations that enable sound recognition and the formation of perceptual categories are largely unknown. Here, using multichannel neural recordings in the auditory midbrain of unanesthetized female rabbits, we first demonstrate that neural ensemble activity in the auditory midbrain displays highly structured correlations that vary with distinct natural sound stimuli. These stimulus-driven correlations can be used to accurately identify individual sounds using single-response trials, even when the sounds do not differ in their spectral content. Combining neural recordings and an auditory model, we then show how correlations between frequency-organized auditory channels can contribute to discrimination of not just individual sounds but sound categories. For both the model and neural data, spectral and temporal correlations achieved similar categorization performance and appear to contribute equally. Moreover, both the neural and model classifiers achieve their best task performance when they accumulate evidence over a time frame of approximately 1-2 seconds, mirroring human perceptual trends. These results together suggest that time-frequency correlations in sounds may be reflected in the correlations between auditory midbrain ensembles and that these correlations may play an important role in the identification and categorization of natural sounds.

The primate brain is specialized for social visual perception. Previous work indicates that recognition draws upon an internal comparison between a viewed face and an internally stored average face. Here we demonstrate that this comparison takes the form of a delayed, dynamic suppression of face averageness among single neurons. In three macaque face patches, spiking responses to low-identity morphed faces met with a synchronous attenuation starting approximately 200 ms after onset. Analysis showed that a late-emerging V-shaped identity tuning was sometimes superimposed on linear ramp tuning. This pattern could not be ascribed to repetition suppression within a given session. The results indicate that the brain’s analysis of faces is enhanced through predictive normalization of identity, which increases sensitivity among face-selective neurons to distinctive facial features known to drive recognition.

Auditory cortex is required for sound localisation, but how neural firing in auditory cortex underlies our perception of sound sources in space remains unclear. Specifically, whether neurons in auditory cortex represent spatial cues or an integrated representation of auditory space across cues is not known. Here, we measured the spatial receptive fields of neurons in primary auditory cortex (A1) while ferrets performed a relative localisation task. Manipulating the availability of binaural and spectral localisation cues had little impact on ferrets’ performance, or on neural spatial tuning. A subpopulation of neurons encoded spatial position consistently across localisation cue type. Furthermore, neural firing pattern decoders outperformed two-channel model decoders using population activity. Together, these observations suggest that A1 encodes the location of sound sources, as opposed to spatial cue values.

Local field potential (LFP) oscillations are primarily shaped by the superposition of postsynaptic currents. Hippocampal LFP oscillations in the 25- to 50-Hz range (“slow γ”) are proposed to support memory retrieval independent of other frequencies. However, θ harmonics extend up to 48 Hz, necessitating a study to determine whether these oscillations are fundamentally the same. We compared the spectral analysis methods of wavelet, ensemble empirical-mode decomposition (EEMD), and Fourier transform. EEMD, as previously applied, failed to account for the θ harmonics. Depending on analytical parameters selected, wavelet may convolve over high-order θ harmonics due to the variable time-frequency atoms, creating the appearance of a broad 25- to 50-Hz rhythm. As an illustration of this issue, wavelet and EEMD depicted slow γ in a synthetic dataset that only contained θ and its harmonics. Oscillatory transience cannot explain the difference in approaches as Fourier decomposition identifies ripples triggered to epochs of high-power, 120- to 250-Hz events. When Fourier is applied to high power, 25- to 50-Hz events, only θ harmonics are resolved. This analysis challenges the identification of the slow γ rhythm as a unique fundamental hippocampal oscillation. While there may be instances in which slow γ is present in the rat hippocampus, the analysis presented here shows that unless care is exerted in the application of EEMD and wavelet techniques, the results may be misleading, in this case misrepresenting θ harmonics. Moreover, it is necessary to reconsider the characteristics that define a fundamental hippocampal oscillation as well as theories based on multiple independent γ bands.

Tactile working memory engages a broad network of cortical regions in primates. To assess whether the conclusions drawn from primates apply to rodents, we examined the vibrissal primary somatosensory cortex (vS1) and the prelimbic cortex (PL) in a delayed comparison task. Rats compared the speeds of two vibrissal vibrations, stimulus1 and stimulus2, separated by a delay of 2 s. Neuronal firing rates in vS1 and PL encode both stimuli in real time. Across the delay, the stimulus1 representation declines more precipitously in vS1 than in PL. Theta-band local field potential (LFP) coherence between vS1 and PL peaks at trial onset and remains elevated during the interstimulus interval; simultaneously, vS1 spikes become phase locked to PL LFP. Phase locking is stronger on correct (versus error) trials. Tactile working memory in rats appears to be mediated by a posterior (vS1) to anterior (PL) flow of information, with performance facilitated through coherent LFP oscillation.

Kinase signaling plays an important role in acquired epilepsy, but only a small percentage of the total kinome has been investigated in this context. A major roadblock that prevents the systematic investigation of the contributions of kinase signaling networks is the slow speed of experiments designed to test the chronic effects of target inhibition in epilepsy models. We developed a novel in vitro screening platform based on microwire recordings from an organotypic hippocampal culture model of acquired epilepsy. This platform enables the direct, parallel determination of the effects of compounds on spontaneous epileptiform activity. The platform also enables repeated recordings from the same culture over two-week long experiments. We screened 45 kinase inhibitors and quantified their effects on seizure duration, the frequency of paroxysmal activity, and electrographic load. We identified several inhibitors with previously unknown antiepileptic properties. We also used kinase inhibition profile cross-referencing to identify kinases that are inhibited by seizure-suppressing compounds, but not by compounds that had no effect on seizures.

Throughout the past decade, silicon-based neural probes have become a driving force in neural engineering. Such probes comprise sophisticated, integrated CMOS electronics which provide a large number of recording sites along slender probe shanks. Using such neural probes in a chronic setting often requires them to be mechanically anchored with respect to the skull. However, any relative motion between brain and implant causes recording instabilities and tissue responses such as glial scarring, thereby shielding recordable neurons from the recording sites integrated on the probe and thus decreasing the signal quality. In the current work, we present a comparison of results obtained using mechanically fixed and floating silicon neural probes chronically implanted into the cortex of a non-human primate. We demonstrate that the neural signal quality estimated by the quality of the spiking and local field potential (LFP) recordings over time is initially superior for the floating probe compared to the fixed device. Nonetheless, the skull-fixed probe also allowed long-term recording of multi-unit activity (MUA) and low frequency signals over several months, especially once pulsations of the brain were properly controlled.

Inferior olivary activity causes both short-term and long-term changes in cerebellar output underlying motor performance and motor learning. Many of its neurons engage in coherent subthreshold oscillations and are extensively coupled via gap junctions. Studies in reduced preparations suggest that these properties promote rhythmic, synchronized output. However, the interaction of these properties with torrential synaptic inputs in awake behaving animals is not well understood. Here we combine electrophysiological recordings in awake mice with a realistic tissue-scale computational model of the inferior olive to study the relative impact of intrinsic and extrinsic mechanisms governing its activity. Our data and model suggest that if subthreshold oscillations are present in the awake state, the period of these oscillations will be transient and variable. Accordingly, by using different temporal patterns of sensory stimulation, we found that complex spike rhythmicity was readily evoked but limited to short intervals of no more than a few hundred milliseconds and that the periodicity of this rhythmic activity was not fixed but dynamically related to the synaptic input to the inferior olive as well as to motor output. In contrast, in the long-term, the average olivary spiking activity was not affected by the strength and duration of the sensory stimulation, while the level of gap junctional coupling determined the stiffness of the rhythmic activity in the olivary network during its dynamic response to sensory modulation. Thus, interactions between intrinsic properties and extrinsic inputs can explain the variations of spiking activity of olivary neurons, providing a temporal framework for the creation of both the short-term and long-term changes in cerebellar output.

The accuracy of the neural code depends on the relative embedding of signal and noise in the activity of neural populations. Despite a wealth of theoretical work on population codes, there are few empirical characterizations of the high-dimensional signal and noise subspaces. We studied the geometry of population codes in the rat auditory cortex across brain states along the activation-inactivation continuum, using sounds varying in difference and mean level across the ears. As the cortex becomes more activated, single-hemisphere populations go from preferring contralateral loud sounds to a symmetric preference across lateralizations and intensities, gain-modulation effectively disappears, and the signal and noise subspaces become approximately orthogonal to each other and to the direction corresponding to global activity modulations. Level-invariant decoding of sound lateralization also becomes possible in the active state. Our results provide an empirical foundation for the geometry and state-dependence of cortical population codes.