Recordings In Non-human Primates Research Articles

Characterization of neural entrainment to speech with and without slow spectral energy fluctuations in laminar recordings in monkey A1

Neural entrainment, the alignment between neural oscillations and rhythmic stimulation, is omnipresent in current theories of speech processing – nevertheless, the underlying neural mechanisms are still largely unknown. Here, we hypothesized that laminar recordings in non-human primates provide us with important insight into these mechanisms, in particular with respect to processing in cortical layers. We presented one monkey with human everyday speech sounds and recorded neural (as current-source density, CSD) oscillations in primary auditory cortex (A1). We observed that the high-excitability phase of neural oscillations was only aligned with those spectral components of speech the recording site was tuned to; the opposite, low-excitability phase was aligned with other spectral components. As low- and high-frequency components in speech alternate, this finding might reflect a particularly efficient way of stimulus processing that includes the preparation of the relevant neuronal populations to the upcoming input. Moreover, presenting speech/noise sounds without systematic fluctuations in amplitude and spectral content and their time-reversed versions, we found significant entrainment in all conditions and cortical layers. When compared with everyday speech, the entrainment in the speech/noise conditions was characterized by a change in the phase relation between neural signal and stimulus and the low-frequency neural phase was dominantly coupled to activity in a lower gamma-band. These results show that neural entrainment in response to speech without slow fluctuations in spectral energy includes a process with specific characteristics that is presumably preserved across species.

On comparing in vivo intracranial recordings in non-human primates to predictions of optimized transcranial electrical stimulation.

Transcranial electrical stimulation (tES) can be optimized to achieve maximal current flow at desired brain regions. The aim of this study was to characterize electric field magnitudes generated by tES optimization and to compare them to experimentally induced values as determined by data from intracranial electrodes. Local field potentials were recorded from two monkeys with implanted multi-site intracranial Utah arrays during transcranial direct current stimulation (tDCS), and the neural effect predictions obtained from optimized electrode placement were assessed. Comparative data between the two sites of intracranial recordings during tDCS partially validated the predictions of our tES optimization algorithms.

Neural mechanisms of selective attention in the somatosensory system.

Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates.

The neuroscience of working memory capacity and training.

Working memory - the ability to maintain and manipulate information over a period of seconds - is a core component of higher cognitive functions. The storage capacity of working memory is limited but can be expanded by training, and evidence of the neural mechanisms underlying this effect is accumulating. Human imaging studies and neurophysiological recordings in non-human primates, together with computational modelling studies, reveal that training increases the activity of prefrontal neurons and the strength of connectivity in the prefrontal cortex and between the prefrontal and parietal cortex. Dopaminergic transmission could have a facilitatory role. These changes more generally inform us of the plasticity of higher cognitive functions.

Upper Beta Band Oscillations in Human Premotor Cortex Encode Subjective Choices in a Vibrotactile Comparison Task.

Comparisons of sequentially presented vibrotactile frequencies have been extensively studied using electrophysiological recordings in nonhuman primates. Although neural signatures for working memory aspects of such tasks were recently also identified in human oscillatory EEG activity, homologue correlates of the comparison process are yet unknown. Here, we recorded EEG activity while participants decided which of two sequentially presented vibrotactile stimuli had a higher frequency. Because choices in this type of task are known to be systematically biased by the time-order effect, we applied Bayesian modeling to account for individual choice behavior. Using model-based EEG analysis, we found that upper beta band amplitude (∼20-30 Hz) was modulated by participants' choices. The modulation emerged ∼750 msec before a behavioral response was given and was source-localized to premotor areas.Importantly, the choice-dependent modulation of beta band amplitude was invariant to different motor response mappings and reflected the categorical outcome of the subjective comparison between the two frequencies. Consistently, this pattern was evident for both correct and incorrect trials, indicating that the beta band amplitude mirrors the internal representation of the comparison outcome. Our data complement previous findings in nonhuman primates and corroborate that the beta band activity in premotor areas reflects the categorical outcome of a sensory comparison prior to translation into an effector-specific motor command.

A silicon based implantable microelectrode array for electrophysiological and dopamine recording from cortex to striatum in the non-human primate brain

Dual-mode, multielectrode recordings have become routine in rodent neuroscience research and have recently been adapted to the non-human primate. However, robust and reliable application of acute, multielectrode recording methods in monkeys especially for deep brain nucleus research remains a challenge. In this paper, We described a low cost silicon based 16-site implantable microelectrode array (MEA) chip fabricated by standard lithography technology for in vivo test. The array was 25mm long and designed to use in non-human primate models, for electrophysiological and electrochemical recording. We presented a detailed protocol for array fabrication, then showed that the device can record Spikes, LFPs and dopamine (DA) variation continuously from cortex to striatum in an esthetized monkey. Though our experiment, high-quality electrophysiological signals were obtained from the animal. Across any given microelectrode, spike amplitudes ranged from 70 to 300μV peak to peak, with a mean signal-to-noise ratio of better than 5:1. Calibration results showed the MEA probe had high sensitivity and good selectivity for DA. The DA concentration changed from 42.8 to 481.6μM when the MEA probe inserted from cortex into deep brain nucleus of striatum, which reflected the inhomogeneous distribution of DA in brains. Compared with existing methods allowing single mode (electrophysiology or electrochemistry) recording. This system is designed explicitly for dual-mode recording to meet the challenges of recording in non-human primates.

A Large-Scale Interface for Optogenetic Stimulation and Recording in Nonhuman Primates

While optogenetics offers great potential for linking brain function and behavior in nonhuman primates, taking full advantage of that potential will require stable access for optical stimulation and concurrent monitoring of neural activity. Here we present a practical, stable interface for stimulation and recording of large-scale cortical circuits. To obtain optogenetic expression across a broad region, here spanning primary somatosensory (S1) and motor (M1) cortices, we used convection-enhanced delivery of the viral vector, with online guidance from MRI. To record neural activity across this region, we used a custom micro-electrocorticographic (μECoG) array designed to minimally attenuate optical stimuli. Lastly, we demonstrated the use of this interface to measure spatiotemporal responses to optical stimulation across M1 and S1. This interface offers a powerful tool for studying circuit dynamics and connectivity across cortical areas, for long-term studies of neuromodulation and targeted cortical plasticity, and for linking these to behavior.

Data-driven model comparing the effects of glial scarring and interface interactions on chronic neural recordings in non-human primates

Objective. We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, and investigated the effects of glial scarring and interface interactions at the electrode recording site on signal quality using a computational model. Approach. A finite-element model of a Utah array microelectrode in neural tissue was coupled with a multi-compartmental model of a neuron to quantify the effects of encapsulation thickness, encapsulation resistivity, and interface resistivity on electrode impedance and waveform amplitude. The coupled model was then reconciled with the in vivo data. Histology was obtained seventeen weeks post-implantation to measure gliosis. Main results. From week 1–3, mean impedance and amplitude increased at rates of 115.8 kΩ/week and 23.1 μV/week, respectively. This initial ramp up in impedance and amplitude was observed across all arrays, and is consistent with biofouling (increasing interface resistivity) and edema clearing (increasing tissue resistivity), respectively, in the model. Beyond week 3, the trends leveled out. Histology showed that thin scars formed around the electrodes. In the model, scarring could not match the in vivo data. However, a thin interface layer at the electrode tip could. Despite having a large effect on impedance, interface resistivity did not have a noticeable effect on amplitude. Significance. This study suggests that scarring does not cause an electrical problem with regard to signal quality since it does not appear to be the main contributor to increasing impedance or significantly affect amplitude unless it displaces neurons. This, in turn, suggests that neural signals can be obtained reliably despite scarring as long as the recording site has sufficiently low impedance after accumulating a thin layer of biofouling. Therefore, advancements in microelectrode technology may be expedited by focusing on improvements to the recording site-tissue interface rather than elimination of the glial scar.

Differences in perceptual learning transfer as a function of training task.

A growing body of research--including results from behavioral psychology, human structural and functional imaging, single-cell recordings in nonhuman primates, and computational modeling--suggests that perceptual learning effects are best understood as a change in the ability of higher-level integration or association areas to read out sensory information in the service of particular decisions. Work in this vein has argued that, depending on the training experience, the "rules" for this read-out can either be applicable to new contexts (thus engendering learning generalization) or can apply only to the exact training context (thus resulting in learning specificity). Here we contrast learning tasks designed to promote either stimulus-specific or stimulus-general rules. Specifically, we compare learning transfer across visual orientation following training on three different tasks: an orientation categorization task (which permits an orientation-specific learning solution), an orientation estimation task (which requires an orientation-general learning solution), and an orientation categorization task in which the relevant category boundary shifts on every trial (which lies somewhere between the two tasks above). While the simple orientation-categorization training task resulted in orientation-specific learning, the estimation and moving categorization tasks resulted in significant orientation learning generalization. The general framework tested here--that task specificity or generality can be predicted via an examination of the optimal learning solution--may be useful in building future training paradigms with certain desired outcomes.

A multi-site array for combined local electrochemistry and electrophysiology in the non-human primate brain

BackgroundCurrently, the primary technique employed in circuit-level study of the brain is electrophysiology, recording local field or action potentials (LFPs or APs). However most communication between neurons is chemical and the relationship between electrical activity within neurons and chemical signaling between them is not well understood in vivo, particularly for molecules that signal at least in part by non-synaptic transmission. New methodWe describe a multi-contact array and accompanying head stage circuit that together enable concurrent electrophysiological and electrochemical recording. The array is small (<200μm) and can be assembled into a device of arbitrary length. It is therefore well-suited for use in all major in vivo model systems in neuroscience, including non-human primates where the large brain and need for daily insertion and removal of recording devices places particularly strict demands on design. ResultsWe present a protocol for array fabrication. We then show that a device built in the manner described can record LFPs and perform enzyme-based amperometric detection of choline in the awake macaque monkey.Comparison with existing methods Existing methods allow single mode (electrophysiology or electrochemistry) recording. This system is designed for concurrent, dual-mode recording. It is also the only system designed explicitly to meet the challenges of recording in non-human primates. ConclusionsOur system offers the possibility for conducting in vivo studies in a range of species that examine the relationship between the electrical activity of neurons and their chemical environment, with exquisite spatial and temporal precision.

Inactivation of Primate Prefrontal Cortex Impairs Auditory and Audiovisual Working Memory.

The ventral frontal lobe, or inferior frontal gyrus, plays an important role in audiovisual communication in the human brain. Studies with nonhuman primates have found that neurons within ventral prefrontal cortex (VLPFC) encode both faces and vocalizations and that VLPFC is active when animals need to remember these social stimuli. In the present study, we temporarily inactivated VLPFC by cooling the cortex while nonhuman primates performed a working memory task. This impaired the ability of subjects to remember a face and vocalization pair or just the vocalization alone. Our work highlights the importance of the primate VLPFC in the processing of faces and vocalizations in a manner that is similar to the inferior frontal gyrus in the human brain.

Macaque monkeys experience visual crowding.

In peripheral vision, objects that are easily discriminated on their own become less discriminable in the presence of surrounding clutter. This phenomenon is known as crowding.The neural mechanisms underlying crowding are not well understood. Better insight might come from single-neuron recording in nonhuman primates, provided they exhibit crowding; however, previous demonstrations of crowding have been confined to humans. In the present study, we set out to determine whether crowding occurs in rhesus macaque monkeys. We found that animals trained to identify a target letter among flankers displayed three hallmarks of crowding as established in humans. First, at a given eccentricity, increasing the spacing between the target and the flankers improved recognition accuracy. Second, the critical spacing, defined as the minimal spacing at which target discrimination was reliable, was proportional to eccentricity. Third, the critical spacing was largely unaffected by object size. We conclude that monkeys, like humans, experience crowding. These findings open the door to studies of crowding at the neuronal level in the monkey visual system.

On the relationship between persistent delay activity, repetition enhancement and priming.

Human efficiency in processing incoming stimuli (in terms of speed and/or accuracy) is typically enhanced by previous exposure to the same, or closely related stimuli—a phenomenon referred to as priming. In spite of the large body of knowledge accumulated in behavioral studies about the conditions conducive to priming, and its relationship with other forms of memory, the underlying neuronal correlates of priming are still under debate. The idea has repeatedly been advanced that a major neuronal mechanism supporting behaviorally-expressed priming is repetition suppression, a widespread reduction of spiking activity upon stimulus repetition which has been routinely exposed by single-unit recordings in non-human primates performing delayed-response, as well as passive fixation tasks. This proposal is mainly motivated by the observation that, in human fMRI studies, priming is associated to a significant reduction of the BOLD signal (widely interpreted as a proxy of the level of spiking activity) upon stimulus repetition. Here, we critically re-examine a large part of the electrophysiological literature on repetition suppression in non-human primates and find that repetition suppression is systematically accompanied by stimulus-selective delay period activity, together with repetition enhancement, an increase of spiking activity upon stimulus repetition in small neuronal populations. We argue that repetition enhancement constitutes a more viable candidate for a putative neuronal substrate of priming, and propose a minimal framework that links together, mechanistically and functionally, repetition suppression, stimulus-selective delay activity and repetition enhancement.

Non-invasive single-trial EEG detection of evoked human neocortical population spikes

QuestionHuman high-frequency (>400Hz) components of somatosensory evoked potentials (hf-SEPs), which can be recorded non-invasively at the scalp, are generated by cortical population spikes, as inferred from microelectrode recordings in non-human primates. It is a critical limitation to broader neurophysiological study of hf-SEPs in that hundreds of responses have to be averaged to detect hf-SEPs reliably. Here, we establish a framework for detecting human hf-SEPs non-invasively in single trials. MethodsSpatio-temporal features were extracted from band-pass filtered (400-900Hz) hf-SEPs by bilinear Common Spatio-Temporal Patterns (bCSTP) and then classified by a weighted Extreme Learning Machine (w-ELM). The effect of varying signal-to-noise ratio (SNR), number of trials, and degree of w-ELM re-weighting was characterized using surrogate data. For practical demonstration of the algorithm, median nerve hf-SEPs were recorded inside a shielded room in four subjects, spanning the hf-SEP signal-to-noise ratio characteristic for a larger population, utilizing a custom-built 29-channel low-noise EEG amplifier. ResultsUsing surrogate data, the SNR proved to be pivotal to detect hf-SEPs in single trials efficiently, with the trade-off between sensitivity and specificity of the algorithm being obtained by the w-ELM re-weighting parameter. In practice, human hf-SEPs were detected non-invasively in single trials with a sensitivity of up to 99% and a specificity of up to 97% in two subjects, even without any recourse to knowledge of stimulus timing. Matching with the results of the surrogate data analysis, these rates dropped to 62–79% sensitivity and 18–31% specificity in two subjects with lower SNR. ConclusionsOtherwise buried in background noise, human high-frequency EEG components can be extracted from low-noise recordings. Specifically, refined supervised filter optimization and classification enables the reliable detection of single-trial hf-SEPs, representing non-invasive correlates of cortical population spikes. SignificanceWhile low-frequency EEG reflects summed postsynaptic potentials, and thereby neuronal input, we suggest that high-frequency EEG (>400Hz) can provide non-invasive access to the unaveraged output of neuronal computation, i.e., single-trial population spike activity evoked in the responsive neuronal ensemble.

Computational modeling and analysis of hippocampal-prefrontal information coding during a spatial decision-making task

We introduce a computational model describing rat behavior and the interactions of neural populations processing spatial and mnemonic information during a maze-based, decision-making task. The model integrates sensory input and implements working memory to inform decisions at a choice point, reproducing rat behavioral data and predicting the occurrence of turn- and memory-dependent activity in neuronal networks subserving task performance. We tested these model predictions using a new software toolbox (Maze Query Language, MQL) to analyse activity of medial prefrontal cortical (mPFC) and dorsal hippocampal (dCA1) neurons recorded from six adult rats during task performance. The firing rates of dCA1 neurons discriminated context (i.e., the direction of the previous turn), whilst a subset of mPFC neurons was selective for current turn direction or context, with some conjunctively encoding both. mPFC turn-selective neurons displayed a ramping of activity on approach to the decision turn and turn-selectivity in mPFC was significantly reduced during error trials. These analyses complement data from neurophysiological recordings in non-human primates indicating that firing rates of cortical neurons correlate with integration of sensory evidence used to inform decision-making.

Functional Topography of Cortical Thumb Movement Representations in Human Primary Motor Cortex

Intracortical microstimulation and single cell recordings in non-human primates showed that both, muscles and movements are represented in primary motor cortex (M1). This was also suggested in humans using electrophysiological and neuroimaging techniques. Transcranial magnetic stimulation (TMS) thus far was used to study motor cortical muscle representations, but data on movement representations in man are scarce. Therefore, we used TMS of M1 to evoke directional (flexion, extension) thumb movements and generated topographic movement maps (TMS-mov-map) in fourteen healthy individuals. TMS-mov-maps were related to the individual voluntary motor output (Vol-mov, directional thumb acceleration). Conventional TMS-motor evoked potentials (TMS-MEP) were simultaneously recorded from the prime movers (flexor and extensor pollicis brevis) and also compared to the voluntary motor output. Remarkably stable topographic maps were generated with both, thumb flexion and extension being multiply represented, overlapped and interspersed. Thumb Flexion was usually more robust than extension. TMS-mov-maps rather than TMS-MEP-maps seemed to better reflect the individual voluntary motor output. The findings emphasize existing models of multiple, overlapping finger movement representations in human M1, and indicate that this model also adapts to antagonistic thumb movements. The results suggest that investigating topographic movement maps may be an interesting adjunct in studying human motor cortical topography and its relevance for motor control.

Representational demands modulate involvement of perirhinal cortex in face processing

The classic view holds that the medial temporal lobes (MTL) are dedicated to declarative memory functioning. Recent evidence, however, suggests that perirhinal cortex (PrC), a structure within the anterior MTL, may also play a role in perceptual discriminations when representations of complex conjunctions of features, or of gestalt-characteristics of objects must be generated. Interestingly, neuroimaging and electrophysiological recordings in nonhuman primates have also revealed a face patch in the anterior collateral sulcus with preferential responses to face stimuli in various task contexts. In the present fMRI study, we investigated the representational demands that influence PrC involvement in different types of judgments on human faces. Holding stimulus complexity constant, we independently manipulated the nature of the task and the orientation of the stimuli presented (through face inversion). Aspects of right PrC showed increased responses in a forced-choice recognition-memory and a perceptual-oddity task, as compared to a feature-search task that was included to probe visual detection of an isolated face feature. Effects of stimulus orientation in right PrC were observed when the recognition-memory condition for upright faces was compared with all other experimental conditions, including recognition-memory for inverted faces-a result that can be related to past work on the role of PrC in object unitization. Notably, both effects in right PrC paralleled activity patterns in broader networks of regions that also included the right fusiform gyrus and the amygdala, regions frequently implicated in face processing in prior research. As such, the current findings do not support the view that reference to a prior study episode clearly distinguishes the role of PrC from that of more posterior ventral visual pathway regions. They add to a growing body of evidence suggesting that the functional role of specific MTL structures may be best understood in terms of the representations that are required by the task and the stimuli at hand.

Effective connectivity in cortical networks underlying visual motion processing and ocular-motor control

Introduction: Human ocular motor functions and visual motion processing have mostly been assumed to rely on segregated networks based on recordings in non-human primates and conventional fMRI studies. Voluntary optokinetic ("look") nystagmus in the horizontal plane, however, contains all essential forms of eye movements whilst at the same time representing a visual motion-tracking task. Aim of the presented approach was to derive an integrative model (“common trunk”) for ocular motor and visual motion networks by means of dynamic causal modeling (DCM).

Where One Hand Meets the Other: Limb-Specific and Action-Dependent Movement Plans Decoded from Preparatory Signals in Single Human Frontoparietal Brain Areas

Planning object-directed hand actions requires successful integration of the movement goal with the acting limb. Exactly where and how this sensorimotor integration occurs in the brain has been studied extensively with neurophysiological recordings in nonhuman primates, yet to date, because of limitations of non-invasive methodologies, the ability to examine the same types of planning-related signals in humans has been challenging. Here we show, using a multivoxel pattern analysis of functional MRI (fMRI) data, that the preparatory activity patterns in several frontoparietal brain regions can be used to predict both the limb used and hand action performed in an upcoming movement. Participants performed an event-related delayed movement task whereby they planned and executed grasp or reach actions with either their left or right hand toward a single target object. We found that, although the majority of frontoparietal areas represented hand actions (grasping vs reaching) for the contralateral limb, several areas additionally coded hand actions for the ipsilateral limb. Notable among these were subregions within the posterior parietal cortex (PPC), dorsal premotor cortex (PMd), ventral premotor cortex, dorsolateral prefrontal cortex, presupplementary motor area, and motor cortex, a region more traditionally implicated in contralateral movement generation. Additional analyses suggest that hand actions are represented independently of the intended limb in PPC and PMd. In addition to providing a unique mapping of limb-specific and action-dependent intention-related signals across the human cortical motor system, these findings uncover a much stronger representation of the ipsilateral limb than expected from previous fMRI findings.

On determining the intracranial sources of visual evoked potentials from scalp topography: A reply to Kelly et al. (this issue)

The cruciform model posits that if a Visual Evoked Potential component originates in cortical area V1, then stimuli placed in the upper versus lower visual field will generate responses with opposite polarity at the scalp. In our original paper (Ales et al., 2010b) we showed that the cruciform model provides an insufficient criterion for identifying V1 sources. This conclusion was reached on the basis of simulations that used realistic 3D models of early visual areas to simulate scalp topographies expected for stimuli of different sizes and shapes placed in different field locations. The simulations indicated that stimuli placed in the upper and lower visual field produce polarity inverting scalp topographies for activation of areas V2 and V3, but not for area V1. As a consequence of the non-uniqueness of the polarity inversion criterion, we suggested that past studies using the cruciform model had not adequately excluded contributions from sources outside V1. In their comment on our paper, Kelly et al. (this issue) raise several concerns with this suggestion. They claim that our initial results did not use the proper stimulus locations to constitute a valid test of the cruciform model. Kelly et al., also contend that the cortical source of the initial visually evoked component (C1) can be identified based on latency and polarity criteria derived from intracranial recordings in non-human primates. In our reply we show that simulations using the suggested critical stimulus locations are consistent with our original findings and thus do not change our conclusions regarding the use of the polarity inversion criterion. We further show that the anatomical assumptions underlying the putatively optimal locations are not consistent with available V1 anatomical data. We then address the non-human primate data, describing how differences in stimuli across studies and species confound an effective utilization of the non-human primate data for interpreting human evoked potential responses. We also show that, considered more broadly, the non-human primate literature shows that multiple visual areas onset simultaneously with V1. We suggest several directions for future research that will further clarify how to make the best use of scalp data for inferring cortical sources.