Recording Of Single-unit Activity Research Articles

Context-invariant beliefs are supported by dynamic reconfiguration of single unit functional connectivity in prefrontal cortex of male macaques

Natural behaviors occur in closed action-perception loops and are supported by dynamic and flexible beliefs abstracted away from our immediate sensory milieu. How this real-world flexibility is instantiated in neural circuits remains unknown. Here, we have male macaques navigate in a virtual environment by primarily leveraging sensory (optic flow) signals, or by more heavily relying on acquired internal models. We record single-unit spiking activity simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and the dorso-lateral prefrontal cortex (dlPFC). Results show that while animals were able to maintain adaptive task-relevant beliefs regardless of sensory context, the fine-grain statistical dependencies between neurons, particularly in 7a and dlPFC, dynamically remapped with the changing computational demands. In dlPFC, but not 7a, destroying these statistical dependencies abolished the area’s ability for cross-context decoding. Lastly, correlational analyses suggested that the more unit-to-unit couplings remapped in dlPFC, and the less they did so in MSTd, the less were population codes and behavior impacted by the loss of sensory evidence. We conclude that dynamic functional connectivity between neurons in prefrontal cortex maintain a stable population code and context-invariant beliefs during naturalistic behavior.

Planar amorphous silicon carbide microelectrode arrays for chronic recording in rat motor cortex

Chronic implantation of intracortical microelectrode arrays (MEAs) capable of recording from individual neurons can be used for the development of brain-machine interfaces. However, these devices show reduced recording capabilities under chronic conditions due, at least in part, to the brain's foreign body response (FBR). This creates a need for MEAs that can minimize the FBR to possibly enable long-term recording. A potential approach to reduce the FBR is the use of MEAs with reduced cross-sectional geometries. Here, we fabricated 4-shank amorphous silicon carbide (a-SiC) MEAs and implanted them into the motor cortex of seven female Sprague-Dawley rats. Each a-SiC MEA shank was 8 μm thick by 20 μm wide and had sixteen sputtered iridium oxide film (SIROF) electrodes (4 per shank). A-SiC was chosen as the fabrication base for its high chemical stability, good electrical insulation properties, and amenability to thin film fabrication. Electrochemical analysis and neural recordings were performed weekly for 4 months. MEAs were characterized pre-implantation in buffered saline and in vivo using electrochemical impedance spectroscopy and cyclic voltammetry at 50 mV/s and 50,000 mV/s. Neural recordings were analyzed for single unit activity. At the end of the study, animals were sacrificed for immunohistochemical analysis. We observed statistically significant, but small, increases in 1 and 30 kHz impedance values and 50,000 mV/s charge storage capacity over the 16-week implantation period. Slow sweep 50 mV/s CV and 1 Hz impedance did not significantly change over time. Impedance values increased from 11.6 MΩ to 13.5 MΩ at 1 Hz, 1.2 MΩ–2.9 MΩ at 1 kHz, and 0.11 MΩ–0.13 MΩ at 30 kHz over 16 weeks. The median charge storage capacity of the implanted electrodes at 50 mV/s was 58.1 mC/cm2 on week 1 and 55.9 mC/cm2 on week 16, and at 50,000 mV/s, 4.27 mC/cm2 on week 1 and 5.93 mC/cm2 on week 16. Devices were able to record neural activity from 92% of all active channels at the beginning of the study, At the study endpoint, a-SiC devices were still recording single-unit activity on 51% of electrochemically active electrode channels. In addition, we observed that the signal-to-noise ratio experienced a small decline of −0.19 per week. We also classified observed units as fast and slow repolarizing based on the trough-to-peak time. Although the overall presence of single units declined, fast and slow repolarizing units declined at a similar rate. At recording electrode depth, immunohistochemistry showed minimal tissue response to the a-SiC devices, as indicated by statistically insignificant differences in activated glial cell response between implanted brains slices and contralateral sham slices at 150 μm away from the implant location, as evidenced by GFAP staining. NeuN staining revealed the presence of neuronal cell bodies close to the implantation site, again statistically not different from a contralateral sham slice. These results warrant further investigation of a-SiC MEAs for future long-term implantation neural recording studies.

Discovering optimal features for neuron-type identification from extracellular recordings.

Advancements in multichannel recordings of single-unit activity (SUA) in vivo present an opportunity to discover novel features of spatially-varying extracellularly-recorded action potentials (EAPs) that are useful for identifying neuron-types. Traditional approaches to classifying neuron-types often rely on computing EAP waveform features based on conventions of single-channel recordings and thus inherit their limitations. However, spatiotemporal EAP waveforms are the product of signals from underlying current sources being mixed within the extracellular space. We introduce a machine learning approach to demix the underlying sources of spatiotemporal EAP waveforms. Using biophysically realistic computational models, we simulate EAP waveforms and characterize them by the relative prevalence of these sources, which we use as features for identifying the neuron-types corresponding to recorded single units. These EAP sources have distinct spatial and multi-resolution temporal patterns that are robust to various sampling biases. EAP sources also are shared across many neuron-types, are predictive of gross morphological features, and expose underlying morphological domains. We then organize known neuron-types into a hierarchy of latent morpho-electrophysiological types based on differences in the source prevalences, which provides a multi-level classification scheme. We validate the robustness, accuracy, and interpretations of our demixing approach by analyzing simulated EAPs from morphologically detailed models with classification and clustering methods. This simulation-based approach provides a machine learning strategy for neuron-type identification.

A Simple, Lightweight, and Low-Cost Customizable Multielectrode Array for Local Field Potential Recordings.

Local field potential (LFP) recording is a valuable method for assessing brain systems communication. Multiple methods have been developed to collect LFP data to study the rhythmic activity of the brain. These methods range from the use of single or bundled metal electrodes to electrode arrays that can target multiple brain regions. Although these electrodes are efficient in collecting LFP activity, they can be expensive, difficult to build, and less adaptable to different applications, which may include targeting multiple brain regions simultaneously. Here, the building process for a 16-channel customizable multielectrode array (CMEA) that can be used to collect LFP data from different brain regions simultaneously in rats is described. These CMEA electrode arrays are lightweight (<1 g), take little time to build (<1 h), and are affordable ($15 Canadian). The CMEA can also be modified to record single-unit and multiunit activity in addition to LFP activity using both wired and wireless neural data acquisition systems. Moreover, these CMEAs can be used to explore neural activity (LFP and single-unit/multiunit activity) in preliminary studies, before purchasing more expensive electrodes for targeted studies. Together, these characteristics make the described CMEA a competitive alternative to the commercially available multielectrode arrays for its simplicity, low cost, and efficiency in collecting LFP data in freely behaving animals.

Spike rates of frontal eye field neurons predict reaction times in a spatial attention task

Which neuronal signal(s) predict reaction times when subjects respond to a target at covertly attended locations? Although recent studies showed that spike rates are not predictive, it remains a highly contested question. Therefore, we record single-unit activity from frontal eye field (FEF) neurons while macaques are performing a covert spatial attention task. We find that the attentional modulation of spike rates of FEF neurons is strongly correlated with behavioral reaction times. Moreover, this correlation already emerges 1s before target dimming, which triggers the behavioral responses. This prediction of reaction times by spike rates is found in neurons showing attention-dependent enhanced and suppressed activity for targets and distractors, respectively, yet in varying degrees across subjects. Thus, spike rates of FEF neurons can predict reaction times persistently and well before the operant behavior during selective attention tasks. Such long prediction windows will be useful for developing spike-based brain-machine interfaces.

Neural correlates of cognitively controlled vocalizations in a corvid songbird

The neuronal basis of the songbird's song system is well understood. However, little is known about the neuronal correlates of the executive control of songbird vocalizations. Here, we record single-unit activity from the pallial endbrain region "nidopallium caudolaterale" (NCL) of crows that vocalize to the presentation of a visual go-cue but refrain from vocalizing during trials without a go-cue. We find that the preparatory activity of single vocalization-correlated neurons, but also of the entire population of NCL neurons, before vocal onset predicts whether or not the crows will produce an instructed vocalization. Fluctuations in baseline neuronal activity prior to the go-cue influence the premotor activity of such vocalization-correlated neurons and seemingly bias the crows' decision to vocalize. Neuronal response modulation significantly differs between volitional and task-unrelated vocalizations. This suggests that the NCL can take control over the vocal motor network during the production of volitional vocalizations in a corvid songbird.

Coding of latent variables in sensory, parietal, and frontal cortices during closed-loop virtual navigation.

We do not understand how neural nodes operate and coordinate within the recurrent action-perception loops that characterize naturalistic self-environment interactions. Here, we record single-unit spiking activity and local field potentials (LFPs) simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and dorsolateral prefrontal cortex (dlPFC) as monkeys navigate in virtual reality to 'catch fireflies'. This task requires animals to actively sample from a closed-loop virtual environment while concurrently computing continuous latent variables: (i) the distance and angle travelled (i.e., path integration) and (ii) the distance and angle to a memorized firefly location (i.e., a hidden spatial goal). We observed a patterned mixed selectivity, with the prefrontal cortex most prominently coding for latent variables, parietal cortex coding for sensorimotor variables, and MSTd most often coding for eye movements. However, even the traditionally considered sensory area (i.e., MSTd) tracked latent variables, demonstrating path integration and vector coding of hidden spatial goals. Further, global encoding profiles and unit-to-unit coupling (i.e., noise correlations) suggested a functional subnetwork composed by MSTd and dlPFC, and not between these and 7a, as anatomy would suggest. We show that the greater the unit-to-unit coupling between MSTd and dlPFC, the more the animals' gaze position was indicative of the ongoing location of the hidden spatial goal. We suggest this MSTd-dlPFC subnetwork reflects the monkeys' natural and adaptive task strategy wherein they continuously gaze toward the location of the (invisible) target. Together, these results highlight the distributed nature of neural coding during closed action-perception loops and suggest that fine-grain functional subnetworks may be dynamically established to subserve (embodied) task strategies.

Brainstem networks construct threat probability and prediction error from neuronal building blocks

When faced with potential threat we must estimate its probability, respond advantageously, and leverage experience to update future estimates. Threat estimation is the proposed domain of the forebrain, while behaviour is elicited by the brainstem. Yet, the brainstem is also a source of prediction error, a learning signal to acquire and update threat estimates. Neuropixels probes allowed us to record single-unit activity across a 21-region brainstem axis in rats receiving probabilistic fear discrimination with foot shock outcome. Against a backdrop of diffuse behaviour signaling, a brainstem network with a dorsal hub signaled threat probability. Neuronal function remapping during the outcome period gave rise to brainstem networks signaling prediction error and shock on multiple timescales. The results reveal brainstem networks construct threat probability, behaviour, and prediction error signals from neuronal building blocks.

Spatial Resolution of Suprachoroidal-Transretinal Stimulation Estimated by Recording Single-Unit Activity From the Cat Lateral Geniculate Nucleus.

Retinal prostheses are devices used to restore visual sensation in patients suffering from photoreceptor degeneration, such as retinitis pigmentosa. Suprachoroidal–transretinal stimulation (STS) is a prosthesis with retinal electrodes located in the sclera. STS has the advantage that it is safer than epiretinal or subretinal prostheses, as the implant is not directly attached to the retinal tissue. We have previously reported feasibility of STS with animal experiments and clinical trials. However, functional evaluation with neurophysiological experiments is still largely missing. To estimate the spatial resolution of STS, single-unit activities in response to STS were recorded from relay cells in the dorsal lateral geniculate nucleus of cats, and the response probability of the units was analyzed in relation to the distance between the stimulus location and the receptive field of each recorded unit. A platinum electrode was attached to the sclera after lamellar resection, and the return electrode was placed in the vitreous. The stimulating current, which ranged from 50 to 500 μA, was applied between these electrodes, and the probability of spike responses occurring just after retinal stimulation was measured. The distance at half-maximum of response was determined from the collected response probabilities as a function of stimulus intensity for all units characterized by their distances from the receptive field center to the stimulation point. As the stimulation became weaker, this distance decreased to 1.8° at 150 and 100 μA. As another estimation, the radius of 25% response probability was 1.4° at 100 μA. The diameter of the stimulated cat retinal area, 3.6° or 2.8°, corresponds to human visual acuity of 0.005 or 0.007, or finger counting. Considering the lower hazard to the retina of STS and its potentially large visual field coverage, STS is an attractive method for retinal prosthetic device development.

Feature-based attention processes in primate prefrontal cortex do not rely on feature similarity.

Feature-based attention enables privileged processing of specific visual properties. During feature-based attention, neurons in visual cortices show "gain modulation" by enhancing neuronal responses to the features of attended stimuli due to top-down signals originating from prefrontal cortex (PFC). Attentional modulation in visual cortices requires "feature similarity:" neurons only increase their responses when the attended feature variable and the neurons' preferred feature coincide. However, whether gain modulation based on feature similarity is a general attentional mechanism is currently unknown. To address this issue, we record single-unit activity from PFC of macaques trained to switch attention between two conjunctive feature parameters. We find that PFC neurons experience gain modulation in response to attentional demands. However, this attentional gain modulation in PFC is independent of the feature-tuning preferences of neurons. These findings suggest that feature similarity is not a general mechanism in feature-based attention throughout the cortical processing hierarchy.

Entrainment of cerebellar Purkinje cell spiking activity using pulsed ultrasound stimulation

BackgroundFocused ultrasound (FUS) has excellent characteristics over other non-invasive stimulation methods in terms of spatial resolution and steering capability of the target. FUS has not been tested in the cerebellar cortex and cellular effects of FUS are not fully understood. Objective/hypothesisTo investigate how the activity of cerebellar Purkinje cells (PCs) is modulated by FUS with varying pulse durations and pulse repetition frequencies. MethodsA glass microelectrode was inserted into the cerebellar vermis lobule 6 from the dorsal side to extracellularly record single unit activity of the PCs in anesthetized rats. Ultrasonic stimulation (500 kHz) was applied through a coupling cone, filled with degassed water, from the posterior side to target the recording area with varying pulse durations and frequencies. ResultsSimple spike (SS) activity of PCs was entrained by the FUS pattern where the probability of spike occurrences peaked at around 1 ms following the onset of the stimulus regardless of its duration (0.5, 1, or 2 ms). The level of entrainment was stronger with shorter pulse durations at 50-Hz pulse repetition frequency (PRF), however, peri-event histograms spread wider and the peaks delayed slightly at 100-Hz PRF, suggesting involvement of a long-lasting inhibitory mechanism. There was no significant difference between the average firing rates in the baseline and stimulation periods. ConclusionFUS can entrain spiking activity of single cells on a spike-by-spike basis as demonstrated here in the rat cerebellar cortex. The observed modulation potentially results from the aggregate of excitatory and inhibitory effects of FUS on the entire cortical network rather than on the PCs alone.

Highly Flexible Single-Unit Resolution All Printed Neural Interface on a Bioresorbable Backbone.

Neural interfaces are the parts of the neural prosthesis that are in contact with the target tissue. The mechanical, chemical, and electrical properties of these interfaces can be a major determinant of the life of the implant and the neural tissue for chronic and even acute integrations. In this work, we developed a fully inkjet-printed, flexible neural interface on a bioresorbable backbone capable of recording high-fidelity neural activity. We utilized room temperature fabrication processes that overcome the limitations of semiconductor fabrication techniques for processing low-melting point polymers while maintaining high spatial and single-cell recording resolution. The ∼8 μm-thick devices in this study were fabricated onto two flexible polymers: (a) polyimide (PI), a biocompatible polymer commonly used for neural interfaces, and (b) polycaprolactone (PCL), a bioresorbable polyester with outstanding mechanical properties. Electrodes for neural recording were built at 30, 50, 75, and 100 μm diameter using silver nanoparticles/(3,4-ethylenedioxytiophene)-poly(styrenesulfonate) (AgNPs/PEDOT:PSS), which through our process achieved the lowest impedance reported in the literature reaching ∼200 Ω at 1 kHz for a 50 μm electrode diameter. We further enhanced the electrochemical performance of AgNPs/PEDOT:PSS by an order of magnitude by incorporating exfoliated graphene into the electrodes. The biocompatibility of the fabricated devices and their ability to record single-unit activity were confirmed by in vitro tests on both rat PC12 cells and isolated neural rat retina, respectively.

CHIME: CMOS-Hosted in vivo Microelectrodes for Massively Scalable Neuronal Recordings.

Mammalian brains consist of 10s of millions to 100s of billions of neurons operating at millisecond time scales, of which current recording techniques only capture a tiny fraction. Recording techniques capable of sampling neural activity at high spatiotemporal resolution have been difficult to scale. The most intensively studied mammalian neuronal networks, such as the neocortex, show a layered architecture, where the optimal recording technology samples densely over large areas. However, the need for application-specific designs as well as the mismatch between the three-dimensional architecture of the brain and largely two-dimensional microfabrication techniques profoundly limits both neurophysiological research and neural prosthetics. Here, we discuss a novel strategy for scalable neuronal recording by combining bundles of glass-ensheathed microwires with large-scale amplifier arrays derived from high-density CMOS in vitro MEA systems or high-speed infrared cameras. High signal-to-noise ratio (<25 μV RMS noise floor, SNR up to 25) is achieved due to the high conductivity of core metals in glass-ensheathed microwires allowing for ultrathin metal cores (down to <1 μm) and negligible stray capacitance. Multi-step electrochemical modification of the tip enables ultra-low access impedance with minimal geometric area, which is largely independent of the core diameter. We show that the microwire size can be reduced to virtually eliminate damage to the blood-brain-barrier upon insertion and we demonstrate that microwire arrays can stably record single-unit activity. Combining microwire bundles and CMOS arrays allows for a highly scalable neuronal recording approach, linking the progress in electrical neuronal recordings to the rapid progress in silicon microfabrication. The modular design of the system allows for custom arrangement of recording sites. Our approach of employing bundles of minimally invasive, highly insulated and functionalized microwires to extend a two-dimensional CMOS architecture into the 3rd dimension can be translated to other CMOS arrays, such as electrical stimulation devices.

Recording of spontaneous vagus nerve activity during Pentylenetetrazol-induced seizures in rats

BackgroundVagus nerve stimulation is a treatment for refractory epilepsy. The vagus nerve carries parasympathetic information and innervates multiple organs. As seizures are commonly associated with autonomic manifestations, we believe that biomarkers for diseases affecting autonomic functions such as epilepsy can be found in vagus nerve signals. New methodWe present a method to record vagus nerve electroneurogram (VENG) and detect in the VENG single unit activity in anesthetized rats during Pentylenetetrazol induced seizures using a true tripolar cuff electrode. ResultsThe VENG consisted of high amplitude bursts and lower amplitude bursts synchronous to respiration and heartbeat respectively. The average spikes exhibited a triphasic shape with duration below 1.5ms and root mean square amplitude varied between 5.5 +/- 0.2 μV and 11.4 +/- 3.1 μV depending on the type of recording. An increase of the contact distance resulted in a signal amplitude increase. Application of Lidocaine led to a total disappearance of the recorded spontaneous spiking of the nerve. Comparison with existing methodsTrue tripolar cuff electrodes exhibited a better performance in terms of artefact rejection, stability and reproducibility of the signal compared to commonly used hook electrodes which is of special interest in seizures where important motion and EMG artifacts are expected. ConclusionWe present a new method to record single unit activity of the vagus nerve during acute chemically induced seizures in rats and verified the neural origin of the recorded signals. This recording method might be a powerful tool to develop seizure biomarkers based on VENG.

Randomized, Double-Blind Assessment of LFP Versus SUA Guidance in STN-DBS Lead Implantation: A Pilot Study.

Background: The efficacy of deep brain stimulation (DBS) therapy in Parkinson’s disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients’ symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent.Methods: Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline.Results: We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, n = 3 STNs). The selected tracks were characterized by higher activity in beta (11–32 Hz) and high-frequency (200–400 Hz) bands (p < 0.01) of LFPs and stronger non-linear coupling between these bands (p < 0.05).Conclusion: Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting.

Sputtered porous Pt for wafer-scale manufacture of low-impedance flexible microelectrodes

Objective. Recording electrical activity from individual cells in vivo is a key technology for basic neuroscience and has growing clinical applications. To maximize the number of independent recording channels as well as the longevity, and quality of these recordings, researchers often turn to small and flexible electrodes that minimize tissue damage and can isolate signals from individual neurons. One challenge when creating these small electrodes, however, is to maintain a low interfacial impedance by applying a surface coating that is stable in tissue and does not significantly complicate the fabrication process. Approach. Here we use a high-pressure Pt sputtering process to create low-impedance electrodes at the wafer scale using standard microfabrication equipment. Main results. We find that direct-sputtered Pt provides a reliable and well-controlled porous coating that reduces the electrode impedance by 5–9 fold compared to flat Pt and is compatible with the microfabrication technologies used to create flexible electrodes. These porous Pt electrodes show reduced thermal noise that matches theoretical predictions. In addition, we show that these electrodes can be implanted into rat cortex, record single unit activity, and be removed all without disrupting the integrity of the coating. We also demonstrate that the shape of the electrode (in addition to the surface area) has a significant effect on the electrode impedance when the feature sizes are on the order of tens of microns. Significance. Overall, porous Pt represents a promising method for manufacturing low-impedance electrodes that can be seamlessly integrated into existing processes for producing flexible neural probes.

Genioglossus motor unit activity in supine and upright postures in obstructive sleep apnea.

This study investigated whether a change in posture affected the activity of the upper-airway dilator muscle genioglossus in participants with and without obstructive sleep apnea (OSA). During wakefulness, a monopolar needle electrode was used to record single motor unit activity in genioglossus in supine and upright positions to alter the gravitational load that causes narrowing of the upper airway. Activity from 472 motor units was recorded during quiet breathing in 17 males, nine of whom had OSA. The mean number of motor units for each participant was 11.8 (SD 3.4) in the upright and 16.0 (SD 4.2) in the supine posture. For respiratory-modulated motor units, there were no significant differences in discharge frequencies between healthy controls and participants with OSA. Within each breath, genioglossus activity increased through the recruitment of phasic motor units and an increase in firing rate, with an overall increase of ~6 Hz (50%) across both postures and participant groups. However, the supine posture did not lead to compensatory increases in the peak discharge frequencies of inspiratory and expiratory motor units, despite the increase in gravitational load on the upper airway. Posture also had no significant effect on the discharge frequency of motor units that showed no respiratory modulation during quiet breathing. We postulate that, in wakefulness, any increase in genioglossus activity to compensate for the gravitational effects on the upper airway is achieved primarily through the recruitment of additional motor units in both healthy controls and participants with OSA.

Orbitofrontal cortex is selectively activated in a primate model of attentional bias to cocaine cues

Attentional bias to drug-associated cues correlates with extent of current use, and risk of relapse among those attempting abstinence. Electroencephalogram (EEG) and functional imaging measures in clinical studies have previously investigated the neural basis of attentional bias, but the lack of animal models precluded investigation at the single-unit level. To complement results obtained from clinical studies, we have employed a non-human primate model of attentional bias to cocaine cues while simultaneously recording single-unit activity in cortical and striatal regions implicated in reward processing. Rhesus macaques conditioned to associate particular colors with cocaine or water reward performed an attentional bias task, in which those colors served as irrelevant distractors. Concurrently, multiple electrode arrays for recording single-unit activity were acutely implanted into the orbitofrontal cortex, anterior cingulate cortex, dorsal anterior striatum, and ventral striatum. As in clinical studies, attentional bias was indicated by elongated response times on trials with cocaine-associated distractors compared with trials with water-associated, or control unconditioned distractors. In both animals studied, across an unbiased sample of neurons, the orbitofrontal cortex differentiated distractor condition by the proportion of single-units activated, as well as by population response. In one of the two, the anterior cingulate cortex did as well, but neither striatal region did in either animal. These direct measures of single-unit activity in a primate model complement clinical imaging observations suggesting that cortical mechanisms, especially in orbitofrontal cortex, are likely involved in attentional bias to cocaine-associated environmental cues.

MEMS-Actuated Carbon Fiber Microelectrode for Neural Recording.

Microwire and microelectrode arrays used for cortical neural recording typically consist of tens to hundreds of recording sites, but often only a fraction of these sites are in close enough proximity to firing neurons to record single-unit activity. Recent work has demonstrated precise, depth-controllable mechanisms for the insertion of single neural recording electrodes, but these methods are mostly only capable of inserting electrodes which elicit an adverse biological response. We present an electrostatic-based actuator capable of inserting individual carbon fiber microelectrodes which elicit minimal to no adverse biological response. The device is shown to insert a carbon fiber recording electrode into an agar brain phantom and can record an artificial neural signal in saline. This technique provides a platform generalizable to many microwire-style recording electrodes.

A new approach for estimation of spiketrain patterns in basal ganglia.

The pathophysiological model of dystonia proposed that in addition to reduced firing rate in the internal pallidum, changes in the pattern may also play a role in disease manifestation. While common methods for patterns separation depends on arbitrary spiketrain parameters, we considered the new method for neural patterns based on spike density histograms and hierarchical clustering of real datasets. We used the single unit activity recordings from the globus pallidus external (GPe) and the globus pallidus internal (GPi) from 10 cervical dystonia (CD), 7 segmental dystonia (SD) and 8 generalized dystonia (GD) patients undergoing deep brain stimulation surgery. Using novel method, we separated three patterns of activity: burst, burst-like and tonic. Using this separation, we revealed the differences both in firing rate and pattern distribution between dystonia patients. We have shown the suitability of the proposed method for pattern clusterization on real data and assume that further application of this method would facilitate more detailed study of the neural activity in the basal ganglia and the search for neurophysiological biomarkers of movement disorders.