Chronic multiunit recordings in behaving animals: advantages and limitations

Comparison of electrical microstimulation artifact removal methods for high-channel-count prostheses

BACKGROUND

Neuroprostheses are used to electrically stimulate the brain, modulate neural activity and restore sensory and motor function following injury or disease, such as blindness, paralysis, and other movement and psychiatric disorders. Recordings are often made simultaneously with stimulation, allowing the monitoring of neural signals and closed-loop control of devices. However, stimulation-evoked artifacts may obscure neural activity, particularly when stimulation and recording sites are nearby. Several methods have been developed to remove stimulation artifacts, but it remains challenging to validate and compare these methods because the 'ground-truth' of the neuronal signals may be contaminated by artifacts.

NEW METHOD

Here, we delivered stimulation to the visual cortex via a high-channel-count prosthesis while recording neuronal activity and stimulation artifacts. We quantified the waveforms and temporal properties of stimulation artifacts from the cortical visual prosthesis (CVP) and used them to build a dataset, in which we simulated the neuronal activity and the stimulation artifacts. We illustrate how to use the simulated data to evaluate the performance of six software-based artifact removal methods (Template subtraction, Linear interpolation, Polynomial fitting, Exponential fitting, SALPA and ERAASR) in a CVP application scenario.

RESULTS

We here focused on stimulation artifacts caused by electrical stimulation through a high-channel-count cortical prosthesis device. We find that the Polynomial fitting and Exponential fitting methods outperform the other methods in recovering spikes and multi-unit activity. Linear interpolation and Template subtraction recovered the local-field potentials.

CONCLUSION

Polynomial fitting and Exponential fitting provided a good trade-off between the quality of the recovery of spikes and multi-unit activity (MUA) and the computational complexity for a cortical prosthesis.

Neural manifolds in V1 change with top-down signals from V4 targeting the foveal region

High-dimensional brain activity is often organized into lower-dimensional neural manifolds. However, the neural manifolds of the visual cortex remain understudied. Here, we study large-scale multi-electrode electrophysiological recordings of macaque (Macaca mulatta) areas V1, V4, and DP with a high spatiotemporal resolution. We find that the population activity of V1 contains two separate neural manifolds, which correlate strongly with eye closure (eyes open/closed) and have distinct dimensionalities. Moreover, we find strong top-down signals from V4 to V1, particularly to the foveal region of V1, which are significantly stronger during the eyes-open periods. Finally, in silico simulations of a balanced spiking neuron network qualitatively reproduce the experimental findings. Taken together, our analyses and simulations suggest that top-down signals modulate the population activity of V1. We postulate that the top-down modulation during the eyes-open periods prepares V1 for fast and efficient visual responses, resulting in a type of visual stand-by state.

Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network

Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.

Neuronal representation of visual working memory content in the primate primary visual cortex

The human ability to perceive vivid memories as if they "float" before our eyes, even in the absence of actual visual stimuli, captivates the imagination. To determine the neural substrates underlying visual memories, we investigated the neuronal representation of working memory content in the primary visual cortex of monkeys. Our study revealed that neurons exhibit unique responses to different memory contents, using firing patterns distinct from those observed during the perception of external visual stimuli. Moreover, this neuronal representation evolves with alterations in the recalled content and extends beyond the retinotopic areas typically reserved for processing external visual input. These discoveries shed light on the visual encoding of memories and indicate avenues for understanding the remarkable power of the mind's eye.

Brain2GAN: Feature-disentangled neural encoding and decoding of visual perception in the primate brain

A challenging goal of neural coding is to characterize the neural representations underlying visual perception. To this end, multi-unit activity (MUA) of macaque visual cortex was recorded in a passive fixation task upon presentation of faces and natural images. We analyzed the relationship between MUA and latent representations of state-of-the-art deep generative models, including the conventional and feature-disentangled representations of generative adversarial networks (GANs) (i.e., z- and w-latents of StyleGAN, respectively) and language-contrastive representations of latent diffusion networks (i.e., CLIP-latents of Stable Diffusion). A mass univariate neural encoding analysis of the latent representations showed that feature-disentangled w representations outperform both z and CLIP representations in explaining neural responses. Further, w-latent features were found to be positioned at the higher end of the complexity gradient which indicates that they capture visual information relevant to high-level neural activity. Subsequently, a multivariate neural decoding analysis of the feature-disentangled representations resulted in state-of-the-art spatiotemporal reconstructions of visual perception. Taken together, our results not only highlight the important role of feature-disentanglement in shaping high-level neural representations underlying visual perception but also serve as an important benchmark for the future of neural coding.

Electrophysiological Signatures of Visual Recognition Memory across All Layers of Mouse V1

In mouse primary visual cortex (V1), familiar stimuli evoke significantly altered responses when compared with novel stimuli. This stimulus-selective response plasticity (SRP) was described originally as an increase in the magnitude of visual evoked potentials (VEPs) elicited in layer 4 (L4) by familiar phase-reversing grating stimuli. SRP is dependent on NMDA receptors (NMDARs) and has been hypothesized to reflect potentiation of thalamocortical (TC) synapses in L4. However, recent evidence indicates that the synaptic modifications that manifest as SRP do not occur on L4 principal cells. To shed light on where and how SRP is induced and expressed in male and female mice, the present study had three related aims: (1) to confirm that NMDAR are required specifically in glutamatergic principal neurons of V1, (2) to investigate the consequences of deleting NMDAR specifically in L6, and (3) to use translaminar electrophysiological recordings to characterize SRP expression in different layers of V1. We find that knock-out (KO) of NMDAR in L6 principal neurons disrupts SRP. Current-source density (CSD) analysis of the VEP depth profile shows augmentation of short latency current sinks in layers 3, 4, and 6 in response to phase reversals of familiar stimuli. Multiunit recordings demonstrate that increased peak firing occurs in response to phase reversals of familiar stimuli across all layers, but that activity between phase reversals is suppressed. Together, these data reveal important aspects of the underlying phenomenology of SRP and generate new hypotheses for the expression of experience-dependent plasticity in V1.SIGNIFICANCE STATEMENT Repeated exposure to stimuli that portend neither reward nor punishment leads to behavioral habituation, enabling organisms to dedicate attention to novel or otherwise significant features of the environment. The neural basis of this process, which is so often dysregulated in neurologic and psychiatric disorders, remains poorly understood. Learning and memory of stimulus familiarity can be studied in mouse visual cortex by measuring electrophysiological responses to simple phase-reversing grating stimuli. The current study advances knowledge of this process by documenting changes in visual evoked potentials (VEPs), neuronal spiking activity, and oscillations in the local field potentials (LFPs) across all layers of mouse visual cortex. In addition, we identify a key contribution of a specific population of neurons in layer 6 (L6) of visual cortex.

Laminar neural dynamics of auditory evoked responses: Computational modeling of local field potentials in auditory cortex of non-human primates

Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Modeling and simulations provide a way to integrate these different types of information to clarify underlying neural mechanisms. In this study, we aimed to shed light on the neural dynamics underlying auditory evoked responses by fitting a rate-based model to LFPs recorded via multi-contact electrodes which simultaneously sampled neural activity across cortical laminae. Recordings included neural population responses to best-frequency (BF) and non-BF tones at four representative sites in primary auditory cortex (A1) of awake monkeys. The model considered major neural populations of excitatory, parvalbumin-expressing (PV), and somatostatin-expressing (SOM) neurons across layers 2/3, 4, and 5/6. Unknown parameters, including the connection strength between the populations, were fitted to the data. Our results revealed similar population dynamics, fitted model parameters, predicted equivalent current dipoles (ECD), tuning curves, and lateral inhibition profiles across recording sites and animals, in spite of quite different extracellular current distributions. We found that PV firing rates were higher in BF than in non-BF responses, mainly due to different strengths of tonotopic thalamic input, whereas SOM firing rates were higher in non-BF than in BF responses due to lateral inhibition. In conclusion, we demonstrate the feasibility of the model-fitting approach in identifying the contributions of cell-type specific population activity to stimulus-evoked LFPs across cortical laminae, providing a foundation for further investigations into the dynamics of neural circuits underlying cortical sensory processing.

Feedforward attentional selection in sensory cortex

Salient objects grab attention because they stand out from their surroundings. Whether this phenomenon is accomplished by bottom-up sensory processing or requires top-down guidance is debated. We tested these alternative hypotheses by measuring how early and in which cortical layer(s) neural spiking distinguished a target from a distractor. We measured synaptic and spiking activity across cortical columns in mid-level area V4 of male macaque monkeys performing visual search for a color singleton. A neural signature of attentional capture was observed in the earliest response in the input layer 4. The magnitude of this response predicted response time and accuracy. Errant behavior followed errant selection. Because this response preceded top-down influences and arose in the cortical layer not targeted by top-down connections, these findings demonstrate that feedforward activation of sensory cortex can underlie attentional priority.

The representation of occluded image regions in area V1 of monkeys and humans

Neuronal activity in the primary visual cortex (V1) is driven by feedforward input from within the neurons' receptive fields (RFs) and modulated by contextual information in regions surrounding the RF. The effect of contextual information on spiking activity occurs rapidly and is therefore challenging to dissociate from feedforward input. To address this challenge, we recorded the spiking activity of V1 neurons in monkeys viewing either natural scenes or scenes where the information in the RF was occluded, effectively removing the feedforward input. We found that V1 neurons responded rapidly and selectively to occluded scenes. V1 responses elicited by occluded stimuli could be used to decode individual scenes and could be predicted from those elicited by non-occluded images, indicating that there is an overlap between visually driven and contextual responses. We used representational similarity analysis to show that the structure of V1 representations of occluded scenes measured with electrophysiology in monkeys correlates strongly with the representations of the same scenes in humans measured with functional magnetic resonance imaging (fMRI). Our results reveal that contextual influences rapidly alter V1 spiking activity in monkeys over distances of several degrees in the visual field, carry information about individual scenes, and resemble those in human V1. VIDEO ABSTRACT.

Electrophysiological characteristics of CM-pf in diagnosis and outcome of patients with disorders of consciousness

BACKGROUND

Deep brain stimulation (DBS) in the centromedian-parafascicular complex (CM-pf) has been reported as a potential therapeutic option for disorders of consciousness (DoC). However, the lack of understanding of its electrophysiological characteristics limits the improvement of therapeutic effect.

OBJECTIVE

To investigate the CM-pf electrophysiological characteristics underlying disorders of consciousness (DoC) and its recovery.

METHODS

We collected the CM-pf electrophysiological signals from 23 DoC patients who underwent central thalamus DBS (CT-DBS) surgery. Five typical electrophysiological features were extracted, including neuronal firing properties, multiunit activity (MUA) properties, signal stability, spike-MUA synchronization strength (syncMUA), and the background noise level. Their correlations with the consciousness level, the outcome, and the primary clinical factors of DoC were analyzed.

RESULTS

11 out of 23 patients (0/2 chronic coma, 5/13 unresponsive wakefulness syndrome/vegetative state (UWS/VS), 6/8 minimally conscious state minus (MCS-)) exhibited an improvement in the level of consciousness after CT-DBS. In CM-pf, significantly stronger gamma band syncMUA strength and alpha band normalized MUA power were found in MCS- patients. In addition, higher firing rates, stronger high-gamma band MUA power and alpha band normalized power, and more stable theta oscillation were correlated with better outcomes. Besides, we also identified electrophysiological properties that are correlated with clinical factors, including etiologies, age, and duration of DoC.

CONCLUSION

We provide comprehensive analyses of the electrophysiological characteristics of CM-pf in DoC patients. Our results support the 'mesocircuit' hypothesis, one proposed mechanism of DoC recovery, and reveal CM-pf electrophysiological features that are crucial for understanding the pathogenesis of DoC, predicting its recovery, and explaining the effect of clinical factors on DoC.

Chronic stability of a neuroprosthesis comprising multiple adjacent Utah arrays in monkeys

Objective. Electrical stimulation of visual cortex via a neuroprosthesis induces the perception of dots of light ('phosphenes'), potentially allowing recognition of simple shapes even after decades of blindness. However, restoration of functional vision requires large numbers of electrodes, and chronic, clinical implantation of intracortical electrodes in the visual cortex has only been achieved using devices of up to 96 channels. We evaluated the efficacy and stability of a 1024-channel neuroprosthesis system in non-human primates (NHPs) over more than 3 years to assess its suitability for long-term vision restoration.Approach.We implanted 16 microelectrode arrays (Utah arrays) consisting of 8 × 8 electrodes with iridium oxide tips in the primary visual cortex (V1) and visual area 4 (V4) of two sighted macaques. We monitored the animals' health and measured electrode impedances and neuronal signal quality by calculating signal-to-noise ratios of visually driven neuronal activity, peak-to-peak voltages of the waveforms of action potentials, and the number of channels with high-amplitude signals. We delivered cortical microstimulation and determined the minimum current that could be perceived, monitoring the number of channels that successfully yielded phosphenes. We also examined the influence of the implant on a visual task after 2-3 years of implantation and determined the integrity of the brain tissue with a histological analysis 3-3.5 years post-implantation.Main results. The monkeys remained healthy throughout the implantation period and the device retained its mechanical integrity and electrical conductivity. However, we observed decreasing signal quality with time, declining numbers of phosphene-evoking electrodes, decreases in electrode impedances, and impaired performance on a visual task at visual field locations corresponding to implanted cortical regions. Current thresholds increased with time in one of the two animals. The histological analysis revealed encapsulation of arrays and cortical degeneration. Scanning electron microscopy on one array revealed degradation of IrOxcoating and higher impedances for electrodes with broken tips.Significance. Long-term implantation of a high-channel-count device in NHP visual cortex was accompanied by deformation of cortical tissue and decreased stimulation efficacy and signal quality over time. We conclude that improvements in device biocompatibility and/or refinement of implantation techniques are needed before future clinical use is feasible.

Optogenetic stimulation of the primary visual cortex drives activity in the visual association cortex

Developing optogenetic methods for research in non-human primates (NHP) is important for translational neuroscience and for delineating brain function with unprecedented specificity. Here we assess, in macaque monkeys, the selectivity by which optogenetic stimulation of the primary visual cortex (V1) drives the local laminar and widespread cortical connectivity related to visual perception. Towards this end, we transfected neurons with light-sensitive channelrhodopsin in dorsal V1. fMRI revealed that optogenetic stimulation of V1 using blue light at 40 Hz increased functional activity in the visual association cortex, including areas V2/V3, V4, motion-sensitive area MT and frontal eye fields, although nonspecific heating and eye movement contributions to this effect could not be ruled out. Neurophysiology and immunohistochemistry analyses confirmed optogenetic modulation of spiking activity and opsin expression with the strongest expression in layer 4-B in V1. Stimulating this pathway during a perceptual decision task effectively elicited a phosphene percept in the receptive field of the stimulated neurons in one monkey. Taken together, our findings demonstrate the great potential of optogenetic methods to drive the large-scale cortical circuits of the primate brain with high functional and spatial specificity.

Electrophysiological signatures of visual recognition memory across all layers of mouse V1

In mouse primary visual cortex (V1), familiar stimuli evoke significantly altered responses when compared to novel stimuli. This stimulus-selective response plasticity (SRP) was described originally as an increase in the magnitude of visual evoked potentials (VEPs) elicited in layer (L) 4 by familiar phase-reversing grating stimuli. SRP is dependent on NMDA receptors (NMDAR) and has been hypothesized to reflect potentiation of thalamocortical synapses in L4. However, recent evidence indicates that the synaptic modifications that manifest as SRP do not occur on L4 principal cells. To shed light on where and how SRP is induced and expressed, the present study had three related aims: (1) to confirm that NMDAR are required specifically in glutamatergic principal neurons of V1, (2) to investigate the consequences of deleting NMDAR specifically in L6, and (3) to use translaminar electrophysiological recordings to characterize SRP expression in different layers of V1. We find that knockout of NMDAR in L6 principal neurons disrupts SRP. Current-source density analysis of the VEP depth profile shows augmentation of short latency current sinks in layers 3, 4 and 6 in response to phase reversals of familiar stimuli. Multiunit recordings demonstrate that increased peak firing occurs to in response to phase reversals of familiar stimuli across all layers, but that activity between phase reversals is suppressed. Together, these data reveal important aspects of the underlying phenomenology of SRP and generate new hypotheses for the expression of experience-dependent plasticity in V1.

Significance Statement

Repeated exposure to stimuli that portend neither reward nor punishment leads to behavioral habituation, enabling organisms to dedicate attention to novel or otherwise significant features of the environment. The neural basis of this process, which is so often dysregulated in neurological and psychiatric disorders, remains poorly understood. Learning and memory of stimulus familiarity can be studied in mouse visual cortex by measuring electrophysiological responses to simple phase-reversing grating stimuli. The current study advances knowledge of this process by documenting changes in visual evoked potentials, neuronal spiking activity, and oscillations in the local field potentials across all layers of mouse visual cortex. In addition, we identify a key contribution of a specific population of neurons in layer 6 of visual cortex.

Multimodal monitoring of human cortical organoids implanted in mice reveal functional connection with visual cortex

Human cortical organoids, three-dimensional neuronal cultures, are emerging as powerful tools to study brain development and dysfunction. However, whether organoids can functionally connect to a sensory network in vivo has yet to be demonstrated. Here, we combine transparent microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human cortical organoids transplanted into the retrosplenial cortex of adult mice. Two-photon imaging shows vascularization of the transplanted organoid. Visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in multi-unit activity (MUA) and gamma power and phase locking of stimulus-evoked MUA with slow oscillations indicate functional integration between the organoid and the host brain. Immunostaining confirms the presence of human-mouse synapses. Implantation of transparent microelectrodes with organoids serves as a versatile in vivo platform for comprehensive evaluation of the development, maturation, and functional integration of human neuronal networks within the mouse brain.

1024-channel electrophysiological recordings in macaque V1 and V4 during resting state

Co-variations in resting state activity are thought to arise from a variety of correlated inputs to neurons, such as bottom-up activity from lower areas, feedback from higher areas, recurrent processing in local circuits, and fluctuations in neuromodulatory systems. Most studies have examined resting state activity throughout the brain using MRI scans, or observed local co-variations in activity by recording from a small number of electrodes. We carried out electrophysiological recordings from over a thousand chronically implanted electrodes in the visual cortex of non-human primates, yielding a resting state dataset with unprecedentedly high channel counts and spatiotemporal resolution. Such signals could be used to observe brain waves across larger regions of cortex, offering a temporally detailed picture of brain activity. In this paper, we provide the dataset, describe the raw and processed data formats and data acquisition methods, and indicate how the data can be used to yield new insights into the ‘background’ activity that influences the processing of visual information in our brain.

Measurement(s)	brain activity measurement • eye movement
Technology Type(s)	extracellular electrophysiology recording • multi-electrode array system • infrared camera
Factor Type(s)	visual stimulation
Sample Characteristic - Organism	Macaca mulatta

Stimulus dependence of directed information exchange between cortical layers in macaque V1

Perception and cognition require the integration of feedforward sensory information with feedback signals. Using different sized stimuli, we isolate spectral signatures of feedforward and feedback signals, and their effect on communication between layers in primary visual cortex of male macaque monkeys. Small stimuli elicited gamma frequency oscillations predominantly in the superficial layers. These Granger-causally originated in upper layer 4 and lower supragranular layers. Unexpectedly, large stimuli generated strong narrow band gamma oscillatory activity across cortical layers. They Granger-causally arose in layer 5, were conveyed through layer six to superficial layers, and violated existing models of feedback spectral signatures. Equally surprising, with large stimuli, alpha band oscillatory activity arose predominantly in granular and supragranular layers and communicated in a feedforward direction. Thus, oscillations in specific frequency bands are dynamically modulated to serve feedback and feedforward communication and are not restricted to specific cortical layers in V1.

A neuronal basis of iconic memory in macaque primary visual cortex

After a briefly presented visual stimulus disappears, observers retain a detailed representation of this stimulus for a short period of time. This sensory storage is called iconic memory. We measured iconic memory in the perception of monkeys and its neuronal correlates in the primary visual cortex (area V1). We determined how many milliseconds extra viewing time iconic memory is worth and how it decays by varying the duration of a brief stimulus and the timing of a mask. The V1 activity that persists after the disappearance of a stimulus predicted accuracy, with a time course resembling the worth and decay of iconic memory. Finally, we examined how iconic memory interacts with attention. A cue presented after the stimulus disappears boosts attentional influences pertaining to a relevant part of the stimulus but only if it appears before iconic memory decayed. Our results relate iconic memory to neuronal activity in early visual cortex.

Corticothalamic feedback sculpts visual spatial integration in mouse thalamus

En route from the retina to the cortex, visual information passes through the dorsolateral geniculate nucleus (dLGN) of the thalamus, where extensive corticothalamic (CT) feedback has been suggested to modulate spatial processing. How this modulation arises from direct excitatory and indirect inhibitory CT feedback pathways remains enigmatic. Here, we show that in awake mice, retinotopically organized cortical feedback sharpens receptive fields (RFs) and increases surround suppression in the dLGN. Guided by a network model indicating that widespread inhibitory CT feedback is necessary to reproduce these effects, we targeted the visual sector of the thalamic reticular nucleus (visTRN) for recordings. We found that visTRN neurons have large RFs, show little surround suppression and exhibit strong feedback-dependent responses to large stimuli. These features make them an ideal candidate for mediating feedback-enhanced surround suppression in the dLGN. We conclude that cortical feedback sculpts spatial integration in the dLGN, likely via recruitment of neurons in the visTRN.

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

Inferring entire spiking activity from local field potentials

Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes. Previous studies have shown that spikes, in the form of single-unit activity (SUA) or multiunit activity (MUA), can be inferred solely from LFPs with moderately good accuracy. SUA and MUA are typically extracted via threshold-based technique which may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). Another type of spiking activity, referred to as entire spiking activity (ESA), can be extracted by a threshold-less, fast, and automated technique and has led to better performance in several tasks. However, its relationship with the LFPs has not been investigated. In this study, we aim to address this issue by inferring ESA from LFPs intracortically recorded from the motor cortex area of three monkeys performing different tasks. Results from long-term recording sessions and across subjects revealed that ESA can be inferred from LFPs with good accuracy. On average, the inference performance of ESA was consistently and significantly higher than those of SUA and MUA. In addition, local motor potential (LMP) was found to be the most predictive feature. The overall results indicate that LFPs contain substantial information about spiking activity, particularly ESA. This could be useful for understanding LFP-spike relationship and for the development of LFP-based BMIs.

Attention differentially modulates multiunit activity in the lateral geniculate nucleus and V1 of macaque monkeys

Attention promotes the selection of behaviorally relevant sensory signals from the barrage of sensory information available. Visual attention modulates the gain of neuronal activity in all visual brain areas examined, although magnitudes of gain modulations vary across areas. For example, attention gain magnitudes in the dorsal lateral geniculate nucleus (LGN) and primary visual cortex (V1) vary tremendously across fMRI measurements in humans and electrophysiological recordings in behaving monkeys. We sought to determine whether these discrepancies are due simply to differences in species or measurement, or more nuanced properties unique to each visual brain area. We also explored whether robust and consistent attention effects, comparable to those measured in humans with fMRI, are observable in the LGN or V1 of monkeys. We measured attentional modulation of multiunit activity in the LGN and V1 of macaque monkeys engaged in a contrast change detection task requiring shifts in covert visual spatial attention. Rigorous analyses of LGN and V1 multiunit activity revealed robust and consistent attentional facilitation throughout V1, with magnitudes comparable to those observed with fMRI. Interestingly, attentional modulation in the LGN was consistently negligible. These findings demonstrate that discrepancies in attention effects are not simply due to species or measurement differences. We also examined whether attention effects correlated with the feature selectivity of recorded multiunits. Distinct relationships suggest that attentional modulation of multiunit activity depends upon the unique structure and function of visual brain areas.

Configuration and dynamics of dominant inspiratory multineuronal activity patterns during eupnea and gasping generation in vitro

The pre-Bötzinger complex (preBötC), located within the ventral respiratory column, produces inspiratory bursts in varying degrees of synchronization/amplitude. This wide range of population burst patterns reflects the flexibility of the preBötC neurons, which is expressed in variations in the onset/offset times of their activations and their activity during the population bursts, with respiratory neurons exhibiting a large cycle-to-cycle timing jitter both at the population activity onset and at the population activity peak, suggesting that respiratory neurons are stochastically activated before and during the inspiratory bursts. However, it is still unknown whether this stochasticity is maintained while evaluating the coactivity of respiratory neuronal ensembles. Moreover, the preBötC topology also remains unknown. In this study, by simultaneously recording tens of preBötC neurons and using coactivation analysis during the inspiratory periods, we found that the preBötC has a scale-free configuration (mixture of not many highly connected nodes, hubs, with abundant poorly connected elements) exhibiting the rich-club phenomenon (hubs more likely interconnected with each other). PreBötC neurons also produce multineuronal activity patterns (MAPs) that are highly stable and change during the hypoxia-induced reconfiguration. Moreover, preBötC contains a coactivating core network shared by all its MAPs. Finally, we found a distinctive pattern of sequential coactivation of core network neurons at the beginning of the inspiratory periods, indicating that, when evaluated at the multicellular level, the coactivation of respiratory neurons seems not to be stochastic.NEW & NOTEWORTHY By means of multielectrode recordings of preBötC neurons, we evaluated their configuration in normoxia and hypoxia, finding that the preBötC exhibits a scale-free configuration with a rich-club phenomenon. preBötC neurons produce multineuronal activity patterns that are highly stable but change during hypoxia. The preBötC contains a coactivating core network that exhibit a distinctive pattern of coactivation at the beginning of inspirations. These results reveal some network basis of inspiratory rhythm generation and its reconfiguration during hypoxia.

Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning

OBJECTIVE

Brain-machine interfaces (BMIs) seek to restore lost motor functions in individuals with neurological disorders by enabling them to control external devices directly with their thoughts. This work aims to improve robustness and decoding accuracy that currently become major challenges in the clinical translation of intracortical BMIs.

APPROACH

We propose entire spiking activity (ESA) -an envelope of spiking activity that can be extracted by a simple, threshold-less, and automated technique- as the input signal. We couple ESA with deep learning-based decoding algorithm that uses quasi-recurrent neural network (QRNN) architecture. We evaluate comprehensively the performance of ESA-driven QRNN decoder for decoding hand kinematics from neural signals chronically recorded from the primary motor cortex area of three non-human primates performing different tasks.

MAIN RESULTS

Our proposed method yields consistently higher decoding performance than any other combinations of the input signal and decoding algorithm previously reported across long term recording sessions. It can sustain high decoding performance even when removing spikes from the raw signals, when using the different number of channels, and when using a smaller amount of training data.

SIGNIFICANCE

Overall results demonstrate exceptionally high decoding accuracy and chronic robustness, which is highly desirable given it is an unresolved challenge in BMIs.

Shape perception via a high-channel-count neuroprosthesis in monkey visual cortex

Blindness affects 40 million people across the world. A neuroprosthesis could one day restore functional vision in the blind. We implanted a 1024-channel prosthesis in areas V1 and V4 of the visual cortex of monkeys and used electrical stimulation to elicit percepts of dots of light (called phosphenes) on hundreds of electrodes, the locations of which matched the receptive fields of the stimulated neurons. Activity in area V4 predicted phosphene percepts that were elicited in V1. We simultaneously stimulated multiple electrodes to impose visible patterns composed of a number of phosphenes. The monkeys immediately recognized them as simple shapes, motions, or letters. These results demonstrate the potential of electrical stimulation to restore functional, life-enhancing vision in the blind.

Responsivity to light in familial hemiplegic migraine type 1 mutant mice reveals frequency-dependent enhancement of visual network excitability

Migraine patients often report (inter)ictal hypersensitivity to light, but the underlying mechanisms remain an enigma. Both hypo- and hyperresponsivity of the visual network have been reported, which may reflect either intra-individual dynamics of the network or large inter-individual variation in the measurement of human visual evoked potential data. Therefore, we studied visual system responsivity in freely behaving mice using combined epidural electroencephalography and intracortical multi-unit activity to reduce variation in recordings and gain insight into visual cortex dynamics. For better clinical translation, we investigated transgenic mice that carry the human pathogenic R192Q missense mutation in the α_1A subunit of voltage-gated Ca_V 2.1 Ca²⁺ channels leading to enhanced neurotransmission and familial hemiplegic migraine type 1 in patients. Visual evoked potentials were studied in response to visual stimulation paradigms with flashes of light. Following intensity-dependent visual stimulation, FHM1 mutant mice displayed faster visual evoked potential responses, with lower initial amplitude, followed by less pronounced neuronal suppression compared to wild-type mice. Similar to what was reported for migraine patients, frequency-dependent stimulation in mutant mice revealed enhanced photic drive in the EEG beta-gamma band. The frequency-dependent increases in visual network responses in mutant mice may reflect the context-dependent enhancement of visual cortex excitability, which could contribute to our understanding of sensory hypersensitivity in migraine.

Reward-Related Suppression of Neural Activity in Macaque Visual Area V4

In order for organisms to survive, they need to detect rewarding stimuli, for example, food or a mate, in a complex environment with many competing stimuli. These rewarding stimuli should be detected even if they are nonsalient or irrelevant to the current goal. The value-driven theory of attentional selection proposes that this detection takes place through reward-associated stimuli automatically engaging attentional mechanisms. But how this is achieved in the brain is not very well understood. Here, we investigate the effect of differential reward on the multiunit activity in visual area V4 of monkeys performing a perceptual judgment task. Surprisingly, instead of finding reward-related increases in neural responses to the perceptual target, we observed a large suppression at the onset of the reward indicating cues. Therefore, while previous research showed that reward increases neural activity, here we report a decrease. More suppression was caused by cues associated with higher reward than with lower reward, although neither cue was informative about the perceptually correct choice. This finding of reward-associated neural suppression further highlights normalization as a general cortical mechanism and is consistent with predictions of the value-driven attention theory.

Dissociation of Unit Activity and Gamma Oscillations during Vocalization in Primate Auditory Cortex

Vocal production is a sensory-motor process in which auditory self-monitoring is used to ensure accurate communication. During vocal production, the auditory cortex of both humans and animals is suppressed, a phenomenon that plays an important role in self-monitoring and vocal motor control. However, the underlying neural mechanisms of this vocalization-induced suppression are unknown. γ-band oscillations (>25 Hz) have been implicated a variety of cortical functions and are thought to arise from activity of local inhibitory interneurons, but have not been studied during vocal production. We therefore examined γ-band activity in the auditory cortex of vocalizing marmoset monkeys, of either sex, and found that γ responses increased during vocal production. This increase in γ contrasts with simultaneously recorded suppression of single-unit and multiunit responses. Recorded vocal γ oscillations exhibited two separable components: a vocalization-specific nonsynchronized ("induced") response correlating with vocal suppression, and a synchronized ("evoked") response that was also present during passive sound playback. These results provide evidence for the role of cortical γ oscillations during inhibitory processing. Furthermore, the two distinct components of the γ response suggest possible mechanisms for vocalization-induced suppression, and may correspond to the sensory-motor integration of top-down and bottom-up inputs to the auditory cortex during vocal production.SIGNIFICANCE STATEMENT Vocal communication is important to both humans and animals. In order to ensure accurate information transmission, we must monitor our own vocal output. Surprisingly, spiking activity in the auditory cortex is suppressed during vocal production yet maintains sensitivity to the sound of our own voice ("feedback"). The mechanisms of this vocalization-induced suppression are unknown. Here we show that auditory cortical γ oscillations, which reflect interneuron activity, are actually increased during vocal production, the opposite response of that seen in spiking units. We discuss these results with proposed functions of γ activity during inhibitory sensory processing and coordination of different brain regions, suggesting a role in sensory-motor integration.

A novel approach for removing micro-stimulation artifacts and reconstruction of broad-band neuronal signals

BACKGROUND

Electrical stimulation is a widely used method in the neurosciences with a variety of application fields. However, stimulation frequently induces large and long-lasting artifacts, which superimpose on the actual neuronal signal. Existing methods were developed for analyzing fast events such as spikes, but are not well suited for the restoration of LFP signals.

NEW METHOD

We developed a method that extracts artifact components while also leaving the LFP components of the neuronal signal intact. We based it on an exponential fit of the average artifact shape, which is subsequently adapted to the individual artifacts amplitude and then subtracted. Importantly, we used for fitting of the individual artifact only a short initial time window, in which the artifact is dominating the superimposition with the neuronal signal. Using this short period ensures that LFP components are not part of the fit, which leaves them unaffected by the subsequent artifact removal.

RESULTS

By using the method presented here, we could diminish the substantial distortions of neuronal signals caused by electrical stimulation to levels that were statistically indistinguishable from the original data. Furthermore, the effect of stimulation on the phases of γ- and β- oscillations was reduced by 85 and 75 %, respectively.

COMPARISON WITH EXISTING METHODS

This approach avoids signal loss as caused by methods cutting out artifacts and minimizes the distortion of the signal's temporal structure as compared to other approaches.

CONCLUSION

The method presented here allows for a successful reconstruction of broad-band signals.

Temporal dynamics of binocular integration in primary visual cortex

Whenever we open our eyes, our brain quickly integrates the two eyes' perspectives into a combined view. This process of binocular integration happens so rapidly that even incompatible stimuli are briefly fused before one eye's view is suppressed in favor of the other (binocular rivalry). The neuronal basis for this brief period of fusion during incompatible binocular stimulation is unclear. Neuroanatomically, the eyes provide two largely separate streams of information that are integrated into a binocular response by the primary visual cortex (V1). However, the temporal dynamics underlying the formation of this binocular response are largely unknown. To address this question, we examined the temporal profile of binocular responses in V1 of fixating monkeys. We found that V1 processes binocular stimuli in a dynamic sequence that comprises at least two distinct temporal phases. An initial transient phase is characterized by enhanced spiking responses for both compatible and incompatible binocular stimuli compared to monocular stimulation. This transient is followed by a sustained response that differed markedly between congruent and incongruent binocular stimulation. Specifically, incompatible binocular stimulation resulted in overall response reduction relative to monocular stimulation (binocular suppression). In contrast, responses to compatible stimuli were either suppressed or enhanced (binocular facilitation) depending on the neurons' ocularity (selectivity for one eye over the other) and laminar location. These results suggest that binocular integration in V1 occurs in at least two sequential steps that comprise initial additive combination of the two eyes' signals followed by widespread differentiation between binocular concordance and discordance.

Emotional Mirror Neurons in the Rat's Anterior Cingulate Cortex

How do the emotions of others affect us? The human anterior cingulate cortex (ACC) responds while experiencing pain in the self and witnessing pain in others, but the underlying cellular mechanisms remain poorly understood. Here we show the rat ACC (area 24) contains neurons responding when a rat experiences pain as triggered by a laser and while witnessing another rat receive footshocks. Most of these neurons do not respond to a fear-conditioned sound (CS). Deactivating this region reduces freezing while witnessing footshocks to others but not while hearing the CS. A decoder trained on spike counts while witnessing footshocks to another rat can decode stimulus intensity both while witnessing pain in another and while experiencing the pain first-hand. Mirror-like neurons thus exist in the ACC that encode the pain of others in a code shared with first-hand pain experience. A smaller population of neurons responded to witnessing footshocks to others and while hearing the CS but not while experiencing laser-triggered pain. These differential responses suggest that the ACC may contain channels that map the distress of another animal onto a mosaic of pain- and fear-sensitive channels in the observer. More experiments are necessary to determine whether painfulness and fearfulness in particular or differences in arousal or salience are responsible for these differential responses.

The Segmentation of Proto-Objects in the Monkey Primary Visual Cortex

During visual perception, the brain enhances the representations of image regions that belong to figures and suppresses those that belong to the background. Natural images contain many regions that initially appear to be part of a figure when analyzed locally (proto-objects) but are actually part of the background if the whole image is considered. These proto-grounds must be correctly assigned to the background to allow correct shape identification and guide behavior. To understand how the brain resolves this conflict between local and global processing, we recorded neuronal activity from the primary visual cortex (V1) of macaque monkeys while they discriminated between n/u shapes that have a central proto-ground region. We studied the fine-grained spatiotemporal profile of neural activity evoked by the n/u shape and found that neural representation of the object proceeded from a coarse-to-fine resolution. Approximately 100 ms after the stimulus onset, the representation of the proto-ground region was enhanced together with the rest of the n/u surface, but after ∼115 ms, the proto-ground was suppressed back to the level of the background. Suppression of the proto-ground was only present in animals that had been trained to perform the shape-discrimination task, and it predicted the choice of the animal on a trial-by-trial basis. Attention enhanced figure-ground modulation, but it had no effect on the strength of proto-ground suppression. The results indicate that the accuracy of scene segmentation is sharpened by a suppressive process that resolves local ambiguities by assigning proto-grounds to the background.

Mouse dLGN Receives Functional Input from a Diverse Population of Retinal Ganglion Cells with Limited Convergence

Mouse vision is based on the parallel output of more than 30 functional types of retinal ganglion cells (RGCs). Little is known about how representations of visual information change between retina and dorsolateral geniculate nucleus (dLGN) of the thalamus, the main relay between retina and cortex. Here, we functionally characterized responses of retrogradely labeled dLGN-projecting RGCs and dLGN neurons to the same set of visual stimuli. We found that many of the previously identified functional RGC types innervate dLGN, which maintained a high degree of functional diversity. Using a linear model to assess functional connectivity between RGC types and dLGN neurons, we found that responses of dLGN neurons could be predicted as linear combination of inputs from on average five RGC types, but only two of those had the strongest functional impact. Thus, mouse dLGN receives functional input from a diverse population of RGC types with limited convergence.

Optimizing the Yield of Multi-Unit Activity by Including the Entire Spiking Activity

Neurophysiological data acquisition using multi-electrode arrays and/or (semi-) chronic recordings frequently has to deal with low signal-to-noise ratio (SNR) of neuronal responses and potential failure of detecting evoked responses within random background fluctuations. Conventional methods to extract action potentials (spikes) from background noise often apply thresholds to the recorded signal, usually allowing reliable detection of spikes when data exhibit a good SNR, but often failing when SNR is poor. We here investigate a threshold-independent, fast, and automated procedure for analysis of low SNR data, based on fullwave-rectification and low-pass filtering the signal as a measure of the entire spiking activity (ESA). We investigate the sensitivity and reliability of the ESA-signal for detecting evoked responses by applying an automated receptive field (RF) mapping procedure to semi-chronically recorded data from primary visual cortex (V1) of five macaque monkeys. For recording sites with low SNR, the usage of ESA improved the detection rate of RFs by a factor of 2.5 in comparison to MUA-based detection. For recording sites with medium and high SNR, ESA delivered 30% more RFs than MUA. This significantly higher yield of ESA-based RF-detection still hold true when using an iterative procedure for determining the optimal spike threshold for each MUA individually. Moreover, selectivity measures for ESA-based RFs were quite compatible with MUA-based RFs. Regarding RF size, ESA delivered larger RFs than thresholded MUA, but size difference was consistent over all SNR fractions. Regarding orientation selectivity, ESA delivered more sites with significant orientation-dependent responses but with somewhat lower orientation indexes than MUA. However, preferred orientations were similar for both signal types. The results suggest that ESA is a powerful signal for applications requiring automated, fast, and reliable response detection, as e.g., brain-computer interfaces and neuroprosthetics, due to its high sensitivity and its independence from user-dependent intervention. Because the full information of the spiking activity is preserved, ESA also constitutes a valuable alternative for offline analysis of data with limited SNR.

Layer 3 Dynamically Coordinates Columnar Activity According to Spatial Context

To reduce statistical redundancy of natural inputs and increase the sparseness of coding, neurons in primary visual cortex (V1) show tuning for stimulus size and surround suppression. This integration of spatial information is a fundamental, context-dependent neural operation involving extensive neural circuits that span across all cortical layers of a V1 column, and reflects both feedforward and feedback processing. However, how spatial integration is dynamically coordinated across cortical layers remains poorly understood. We recorded single- and multiunit activity and local field potentials across V1 layers of awake mice (both sexes) while they viewed stimuli of varying size and used dynamic Bayesian model comparisons to identify when laminar activity and interlaminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, where suppression is established within ∼10 ms after response onset, and receptive fields dynamically sharpen while suppression strength increases. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for connections from L3 targeting L5 and L1. Together, the results shed light on the different functional roles of cortical layers in spatial integration and on how L3 dynamically coordinates activity across a cortical column depending on spatial context.SIGNIFICANCE STATEMENT Neurons in primary visual cortex (V1) show tuning for stimulus size, where responses to stimuli exceeding the receptive field can be suppressed (surround suppression). We demonstrate that functional connectivity between V1 layers can also have a surround-suppressed profile. A particularly prominent role seems to have layer 3, the functional connections to layers 5 and 1 of which are strongest for stimuli of optimal size and decreased for large stimuli. Our results therefore point toward a key role of layer 3 in coordinating activity across the cortical column according to spatial context.

Spiking Suppression Precedes Cued Attentional Enhancement of Neural Responses in Primary Visual Cortex

Attending to a visual stimulus increases its detectability, even if gaze is directed elsewhere. This covert attentional selection is known to enhance spiking across many brain areas, including the primary visual cortex (V1). Here we investigate the temporal dynamics of attention-related spiking changes in V1 of macaques performing a task that separates attentional selection from the onset of visual stimulation. We found that preceding attentional enhancement there was a sharp, transient decline in spiking following presentation of an attention-guiding cue. This disruption of V1 spiking was not observed in a task-naïve subject that passively observed the same stimulus sequence, suggesting that sensory activation is insufficient to cause suppression. Following this suppression, attended stimuli evoked more spiking than unattended stimuli, matching previous reports of attention-related activity in V1. Laminar analyses revealed a distinct pattern of activation in feedback-associated layers during both the cue-induced suppression and subsequent attentional enhancement. These findings suggest that top-down modulation of V1 spiking can be bidirectional and result in either suppression or enhancement of spiking responses.

Figure-ground perception in the awake mouse and neuronal activity elicited by figure-ground stimuli in primary visual cortex

Figure-ground segregation is the process by which the visual system identifies image elements of figures and segregates them from the background. Previous studies examined figure-ground segregation in the visual cortex of monkeys where figures elicit stronger neuronal responses than backgrounds. It was demonstrated in anesthetized mice that neurons in the primary visual cortex (V1) of mice are sensitive to orientation contrast, but it is unknown whether mice can perceptually segregate figures from a background. Here, we examined figure-ground perception of mice and found that mice can detect figures defined by an orientation that differs from the background while the figure size, position or phase varied. Electrophysiological recordings in V1 of awake mice revealed that the responses elicited by figures were stronger than those elicited by the background and even stronger at the edge between figure and background. A figural response could even be evoked in the absence of a stimulus in the V1 receptive field. Current-source-density analysis suggested that the extra activity was caused by synaptic inputs into layer 2/3. We conclude that the neuronal mechanisms of figure-ground segregation in mice are similar to those in primates, enabling investigation with the powerful techniques for circuit analysis now available in mice.

Cochlear Synaptopathy Changes Sound-Evoked Activity Without Changing Spontaneous Discharge in the Mouse Inferior Colliculus

Tinnitus and hyperacusis are life-disrupting perceptual abnormalities that are often preceded by acoustic overexposure. Animal models of overexposure have suggested a link between these phenomena and neural hyperactivity, i.e., elevated spontaneous rates (SRs) and sound-evoked responses. Prior work has focused on changes in central auditory responses, with less attention paid to the exact nature of the associated cochlear damage. The demonstration that acoustic overexposure can cause cochlear neuropathy without permanent threshold elevation suggests cochlear neuropathy per se may be a key elicitor of neural hyperactivity. We addressed this hypothesis by recording responses in the mouse inferior colliculus (IC) following a bilateral, neuropathic noise exposure. One to three weeks post-exposure, mean SRs were unchanged in mice recorded while awake, or under anesthesia. SRs were also unaffected by more intense, or unilateral exposures. These results suggest that neither neuropathy nor hair cell loss are sufficient to raise SRs in the IC, at least in 7-week-old mice, 1-3 weeks post exposure. However, it is not clear whether our mice had tinnitus. Tone-evoked rate-level functions at the CF were steeper following exposure, specifically in the region of maximal neuropathy. Furthermore, suppression driven by off-CF tones and by ipsilateral noise were reduced. Both changes were especially pronounced in neurons of awake mice. This neural hypersensitivity may manifest as behavioral hypersensitivity to sound - prior work reports that this same exposure causes elevated acoustic startle. Together, these results indicate that neuropathy may initiate a compensatory response in the central auditory system leading to the genesis of hyperacusis.

Perceptual learning of fine contrast discrimination changes neuronal tuning and population coding in macaque V4

Perceptual learning, the improvement in perceptual abilities with training, is thought to be mediated by an alteration of neuronal tuning. It remains poorly understood how tuning properties change as training progresses, whether improved stimulus tuning directly links to increased behavioural readout of sensory information, or how population coding mechanisms change with training. Here, we recorded continuously from multiple neuronal clusters in area V4 while macaque monkeys learned a fine contrast categorization task. Training increased neuronal coding abilities by shifting the steepest point of contrast response functions towards the categorization boundary. Population coding accuracy of difficult discriminations resulted largely from an increased information coding of individual channels, particularly for those channels that in early learning had larger ability for easy discriminations, but comparatively small encoding abilities for difficult discriminations. Population coding was also enhanced by specific changes in correlations. Neuronal activity became more indicative of upcoming choices with training.

Perceptual learning, the improvement in perceptual abilities with training, is thought to involve changes in neuronal 'tuning'. Here, the authors show that perceptual learning works by making neurons increasingly sensitive to task-relevant differences in stimuli, and by improving population coding mechanisms.

Attention Configures Synchronization Within Local Neuronal Networks for Processing of the Behaviorally Relevant Stimulus

The need for fast and dynamic processing of relevant information imposes high demands onto the flexibility and efficiency of the nervous system. A good example for such flexibility is the attention-dependent selection of relevant sensory information. Studies investigating attentional modulations of neuronal responses to simultaneously arriving input showed that neurons respond, as if only the attended stimulus would be present within their receptive fields (RF). However, attention also improves neuronal representation and behavioral performance, when only one stimulus is present. Thus, attention serves for selecting relevant input and changes the neuronal processing of signals representing selected stimuli, ultimately leading to a more efficient behavioral performance. Here, we tested the hypothesis that attention configures the strength of functional coupling between a local neuronal network's neurons specifically for effective processing of signals representing attended stimuli. This coupling is measured as the strength of γ-synchronization between these neurons. The hypothesis predicts that the pattern of synchronization in local networks should depend on which stimulus is attended. Furthermore, we expect this pattern to be similar for the attended stimulus presented alone or together with irrelevant stimuli in the RF. To test these predictions, we recorded spiking-activity and local field potentials (LFP) with closely spaced electrodes in area V4 of monkeys performing a demanding attention task. Our results show that the γ-band phase coherence (γ-PhC) between spiking-activity and the LFP, as well as the spiking-activity of two groups of neurons, strongly depended on which of the two stimuli in the RF was attended. The γ-PhC was almost identical for the attended stimulus presented either alone or together with a distractor. The functional relevance of dynamic γ-band synchronization is further supported by the observation of strongly degraded γ-PhC before behavioral errors, while firing rates were barely affected. These qualitatively different results point toward a failure of attention-dependent top-down mechanisms to correctly synchronize the local neuronal network in V4, even though this network receives the correctly selected input. These findings support the idea of a flexible, demand-dependent dynamic configuration of local neuronal networks, for performing different functions, even on the same sensory input.

Theta Rhythmic Neuronal Activity and Reaction Times Arising from Cortical Receptive Field Interactions during Distributed Attention

Growing evidence suggests that distributed spatial attention may invoke theta (3-9 Hz) rhythmic sampling processes. The neuronal basis of such attentional sampling is, however, not fully understood. Here we show using array recordings in visual cortical area V4 of two awake macaques that presenting separate visual stimuli to the excitatory center and suppressive surround of neuronal receptive fields (RFs) elicits rhythmic multi-unit activity (MUA) at 3-6 Hz. This neuronal rhythm did not depend on small fixational eye movements. In the context of a distributed spatial attention task, during which the monkeys detected a spatially and temporally uncertain target, reaction times (RTs) exhibited similar rhythmic fluctuations. RTs were fast or slow depending on the target occurrence during high or low MUA, resulting in rhythmic MUA-RT cross-correlations at theta frequencies. These findings show that theta rhythmic neuronal activity can arise from competitive RF interactions and that this rhythm may result in rhythmic RTs potentially subserving attentional sampling.

Auditory cortical activity drives feedback-dependent vocal control in marmosets

Vocal communication is a sensory-motor process requiring auditory self-monitoring to correct errors and to ensure accurate vocal production. When presented with altered speech feedback, humans rapidly change their speech to compensate. Although previous evidence has demonstrated suppression of auditory cortex during both speech and animal vocalization, the specific role of auditory cortex in such feedback-dependent control is unknown. Here we show the relationship between neural activity in the auditory cortex and feedback-dependent vocal control in marmoset monkeys. We demonstrate that marmosets, like humans, exhibit feedback control of vocal acoustics. We further show that feedback-sensitive activity of auditory cortex neurons predict such compensatory vocal changes. Finally, we demonstrate that electrical microstimulation of auditory cortex rapidly evokes similar changes in vocal production. These results are evidence for a causal role of auditory cortex in vocal self-monitoring and feedback-dependent control, and have implications for understanding human speech motor control.

During vocalization, mammals change their vocal production to compensate for altered auditory feedback. Here, Eliades and Tsunada show that neural activity in the marmoset’s auditory cortex mediates this effect, and that stimulation of the auditory cortex evokes similar changes in vocalization.

The threshold for conscious report: Signal loss and response bias in visual and frontal cortex

Why are some visual stimuli consciously detected, whereas others remain subliminal? We investigated the fate of weak visual stimuli in the visual and frontal cortex of awake monkeys trained to report stimulus presence. Reported stimuli were associated with strong sustained activity in the frontal cortex, and frontal activity was weaker and quickly decayed for unreported stimuli. Information about weak stimuli could be lost at successive stages en route from the visual to the frontal cortex, and these propagation failures were confirmed through microstimulation of area V1. Fluctuations in response bias and sensitivity during perception of identical stimuli were traced back to prestimulus brain-state markers. A model in which stimuli become consciously reportable when they elicit a nonlinear ignition process in higher cortical areas explained our results.

Nonparametric test for connectivity detection in multivariate autoregressive networks and application to multiunit activity data

Directed connectivity inference has become a cornerstone in neuroscience to analyze multivariate data from neuroimaging and electrophysiological techniques. Here we propose a nonparametric significance method to test the nonzero values of multivariate autoregressive model to infer interactions in recurrent networks. We use random permutations or circular shifts of the original time series to generate the null-hypothesis distributions. The underlying network model is the same as used in multivariate Granger causality, but our test relies on the autoregressive coefficients instead of error residuals. By means of numerical simulation over multiple network configurations, we show that this method achieves a good control of false positives (type 1 error) and detects existing pairwise connections more accurately than using the standard parametric test for the ratio of error residuals. In practice, our method aims to detect temporal interactions in real neuronal networks with nodes possibly exhibiting redundant activity. As a proof of concept, we apply our method to multiunit activity (MUA) recorded from Utah electrode arrays in a monkey and examine detected interactions between 25 channels. We show that during stimulus presentation our method detects a large number of interactions that cannot be solely explained by the increase in the MUA level.

Transcranial Direct Current Stimulation Facilitates Associative Learning and Alters Functional Connectivity in the Primate Brain

There has been growing interest in transcranial direct current stimulation (tDCS), a non-invasive technique purported to modulate neural activity via weak, externally applied electric fields. Although some promising preliminary data have been reported for applications ranging from stroke rehabilitation to cognitive enhancement, little is known about how tDCS affects the human brain, and some studies have concluded that it may have no effect at all. Here, we describe a macaque model of tDCS that allows us to simultaneously examine the effects of tDCS on brain activity and behavior. We find that applying tDCS to right prefrontal cortex improves monkeys' performance on an associative learning task. While firing rates do not change within the targeted area, tDCS does induce large low-frequency oscillations in the underlying tissue. These oscillations alter functional connectivity, both locally and between distant brain areas, and these long-range changes correlate with tDCS's effects on behavior. Together, these results are consistent with the idea that tDCS leads to widespread changes in brain activity and suggest that it may be a valuable method for cheaply and non-invasively altering functional connectivity in humans.

A Crucial Test of the Population Separation Model of Auditory Stream Segregation in Macaque Primary Auditory Cortex

An important aspect of auditory scene analysis is auditory stream segregation-the organization of sound sequences into perceptual streams reflecting different sound sources in the environment. Several models have been proposed to account for stream segregation. According to the "population separation" (PS) model, alternating ABAB tone sequences are perceived as a single stream or as two separate streams when "A" and "B" tones activate the same or distinct frequency-tuned neuronal populations in primary auditory cortex (A1), respectively. A crucial test of the PS model is whether it can account for the observation that A and B tones are generally perceived as a single stream when presented synchronously, rather than in an alternating pattern, even if they are widely separated in frequency. Here, we tested the PS model by recording neural responses to alternating (ALT) and synchronous (SYNC) tone sequences in A1 of male macaques. Consistent with predictions of the PS model, a greater effective tonotopic separation of A and B tone responses was observed under ALT than under SYNC conditions, thus paralleling the perceptual organization of the sequences. While other models of stream segregation, such as temporal coherence, are not excluded by the present findings, we conclude that PS is sufficient to account for the perceptual organization of ALT and SYNC sequences and thus remains a viable model of auditory stream segregation.SIGNIFICANCE STATEMENT According to the population separation (PS) model of auditory stream segregation, sounds that activate the same or separate neural populations in primary auditory cortex (A1) are perceived as one or two streams, respectively. It is unclear, however, whether the PS model can account for the perception of sounds as a single stream when they are presented synchronously. Here, we tested the PS model by recording neural responses to alternating (ALT) and synchronous (SYNC) tone sequences in macaque A1. A greater effective separation of tonotopic activity patterns was observed under ALT than under SYNC conditions, thus paralleling the perceptual organization of the sequences. Based on these findings, we conclude that PS remains a plausible neurophysiological model of auditory stream segregation.

Distinct Feedforward and Feedback Effects of Microstimulation in Visual Cortex Reveal Neural Mechanisms of Texture Segregation

The visual cortex is hierarchically organized, with low-level areas coding for simple features and higher areas for complex ones. Feedforward and feedback connections propagate information between areas in opposite directions, but their functional roles are only partially understood. We used electrical microstimulation to perturb the propagation of neuronal activity between areas V1 and V4 in monkeys performing a texture-segregation task. In both areas, microstimulation locally caused a brief phase of excitation, followed by inhibition. Both these effects propagated faithfully in the feedforward direction from V1 to V4. Stimulation of V4, however, caused little V1 excitation, but it did yield a delayed suppression during the late phase of visually driven activity. This suppression was pronounced for the V1 figure representation and weaker for background representations. Our results reveal functional differences between feedforward and feedback processing in texture segregation and suggest a specific modulating role for feedback connections in perceptual organization.

Hippocampal gamma-band Synchrony and pupillary responses index memory during visual search

Memory for scenes is supported by the hippocampus, among other interconnected structures, but the neural mechanisms related to this process are not well understood. To assess the role of the hippocampus in memory-guided scene search, we recorded local field potentials and multiunit activity from the hippocampus of macaques as they performed goal-directed search tasks using natural scenes. We additionally measured pupil size during scene presentation, which in humans is modulated by recognition memory. We found that both pupil dilation and search efficiency accompanied scene repetition, thereby indicating memory for scenes. Neural correlates included a brief increase in hippocampal multiunit activity and a sustained synchronization of unit activity to gamma band oscillations (50-70 Hz). The repetition effects on hippocampal gamma synchronization occurred when pupils were most dilated, suggesting an interaction between aroused, attentive processing and hippocampal correlates of recognition memory. These results suggest that the hippocampus may support memory-guided visual search through enhanced local gamma synchrony. © 2016 Wiley Periodicals, Inc.

Layer-specificity in the effects of attention and working memory on activity in primary visual cortex

Neuronal activity in early visual cortex depends on attention shifts but the contribution to working memory has remained unclear. Here, we examine neuronal activity in the different layers of the primary visual cortex (V1) in an attention-demanding and a working memory task. A current-source density analysis reveales top-down inputs in the superficial layers and layer 5, and an increase in neuronal firing rates most pronounced in the superficial and deep layers and weaker in input layer 4. This increased activity is strongest in the attention task but it is also highly reliable during working memory delays. A visual mask erases the V1 memory activity, but it reappeares at a later point in time. These results provide new insights in the laminar circuits involved in the top-down modulation of activity in early visual cortex in the presence and absence of visual stimuli.