Using camera-guided electrode microdrive navigation for precise 3D targeting of macaque brain sites.

Spatial accuracy in electrophysiological investigations is paramount, as precise localization and reliable access to specific brain regions help the advancement of our understanding of the brain's complex neural activity. Here, we introduce a novel, multi camera-based, frameless neuronavigation technique for precise, 3-dimensional electrode positioning in awake monkeys. The investigation of neural functions in awake primates often requires stable access to the brain with thin and delicate recording electrodes. This is usually realized by implanting a chronic recording chamber onto the skull of the animal that allows direct access to the dura. Most recording and positioning techniques utilize this implanted recording chamber as a holder of the microdrive or to hold a grid. This in turn reduces the degrees of freedom in positioning. To solve this problem, we require innovative, flexible, but precise tools for neuronal recordings. We instead mount the electrode microdrive above the animal on an arch, equipped with a series of translational and rotational micromanipulators, allowing movements in all axes. Here, the positioning is controlled by infrared cameras tracking the location of the microdrive and the monkey, allowing precise and flexible trajectories. To verify the accuracy of this technique, we created iron deposits in the tissue that could be detected by MRI. Our results demonstrate a remarkable precision with the confirmed physical location of these deposits averaging less than 0.5 mm from their planned position. Pilot electrophysiological recordings additionally demonstrate the accuracy and flexibility of this method. Our innovative approach could significantly enhance the accuracy and flexibility of neural recordings, potentially catalyzing further advancements in neuroscientific research.

Phase of neural oscillations as a reference frame for attention-based routing in visual cortex.

Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (∼20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modeling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events.

Orchestration of saccadic eye-movements by brain rhythms in macaque Frontal Eye Field.

Visual perception has been suggested to operate on temporal 'chunks' of sensory input, rather than on a continuous stream of visual information. Saccadic eye movements impose a natural rhythm on the sensory input, as periods of steady fixation between these rapid eye movements provide distinct temporal segments of information. Ideally, the timing of saccades should be precisely locked to the brain's rhythms of information processing. Here, we investigated such locking of saccades to rhythmic neural activity in rhesus monkeys performing a visual foraging task. We found that saccades are phase-locked to local field potential oscillations (especially, 9-22 Hz) in the Frontal Eye Field, with the phase of oscillations predictive of the saccade onset as early as 100 ms prior to these movements. Our data also indicate a functional role of this phase-locking in determining the direction of saccades. These findings show a tight-and likely important-link between oscillatory brain activity and rhythmic behavior that imposes a rhythmic temporal structure on sensory input, such as saccadic eye movements.

Forecasting influenza hemagglutinin mutations through the lens of anomaly detection.

The influenza virus hemagglutinin is an important part of the virus attachment to the host cells. The hemagglutinin proteins are one of the genetic regions of the virus with a high potential for mutations. Due to the importance of predicting mutations in producing effective and low-cost vaccines, solutions that attempt to approach this problem have recently gained significant attention. A historical record of mutations has been used to train predictive models in such solutions. However, the imbalance between mutations and preserved proteins is a big challenge for the development of such models that need to be addressed. Here, we propose to tackle this challenge through anomaly detection (AD). AD is a well-established field in Machine Learning (ML) that tries to distinguish unseen anomalies from normal patterns using only normal training samples. By considering mutations as anomalous behavior, we could benefit existing rich solutions in this field that have emerged recently. Such methods also fit the problem setup of extreme imbalance between the number of unmutated vs. mutated training samples. Motivated by this formulation, our method tries to find a compact representation for unmutated samples while forcing anomalies to be separated from the normal ones. This helps the model to learn a shared unique representation between normal training samples as much as possible, which improves the discernibility and detectability of mutated samples from the unmutated ones at the test time. We conduct a large number of experiments on four publicly available datasets, consisting of three different hemagglutinin protein datasets, and one SARS-CoV-2 dataset, and show the effectiveness of our method through different standard criteria.

Dynamic coupling of oscillatory neural activity and its roles in visual attention.

Oscillatory neural activity is believed to have a central role in information processing in the mammalian brain. While early studies often focussed on the function of individual frequency bands, there is emerging appreciation for the role of simultaneous activity in many distinct frequency bands and the interactions between them in high-level cognitive functions. Here, we focus on the role of cross-frequency coupling (CFC) in visual attention. First, we propose a framework that reconciles previous contrasting findings, showing how CFC could have a functional role on both intra- and interareal scales. Second, we outline how CFC between distinct frequency bands could label different submodalities of sensory information. Overall, our scheme provides a novel perspective of how interfrequency interaction contributes to efficient and dynamic processing of information across the brain.

A Deep Learning-Based Approach to Video-Based Eye Tracking for Human Psychophysics.

Real-time gaze tracking provides crucial input to psychophysics studies and neuromarketing applications. Many of the modern eye-tracking solutions are expensive mainly due to the high-end processing hardware specialized for processing infrared-camera pictures. Here, we introduce a deep learning-based approach which uses the video frames of low-cost web cameras. Using DeepLabCut (DLC), an open-source toolbox for extracting points of interest from videos, we obtained facial landmarks critical to gaze location and estimated the point of gaze on a computer screen via a shallow neural network. Tested for three extreme poses, this architecture reached a median error of about one degree of visual angle. Our results contribute to the growing field of deep-learning approaches to eye-tracking, laying the foundation for further investigation by researchers in psychophysics or neuromarketing.

As Evidence-Based Tumorigenic Role of Epstein-Barr Virus miR-BART1-3p in Neurological Tumors.

INTRODUCTION: Central nervous system tumors are a diverse group of tumors that account for 2% of all adult cancers and 17% of childhood malignancies. Several internal and external risk factors are involved in the development of this cancer such as viral infections. The aim of this study was to the determination of the EBV infection frequency and the expression level of miR-122 and miR-BART in CNS tumors samples. METHODS: One hundred and thirty-eight  fresh tissue sample (106 case and 32 control) was collected from CNS specimens. The presence of Epstein-Barr virus (EBV) DNA was examined by PCR assay and the expression level of miR-122 and miR-BART were evaluated by using real-time PCR assay in CNS tissue samples. RESULTS: EBV DNA was detected in 17% (18 of 106) of tumors tissue samples and 6.4% (2 of 32) of control samples. according to results, there was a significant relationship between the presence of EBV-DNA with CNS tumors. Additionally, the expression level of miR-122 was significantly downregulated in the EBV-positive sample compared to that of the EBV-negative sample. Also, the level of EBV-BART1-3p expression was significantly higher in EBV-positive tumors samples than EBV-positive normal samples. CONCLUSION: The results of this study suggest that the EBV could change the condition of cancer cells by altering the expression of miR-122 and EBV-BART1-3p and maybe contribute to the development of cancer cells. However, the role of viral infections in CNS cancer requires further studies. 
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A neural correlate of visual feature binding in primate lateral prefrontal cortex.

We effortlessly perceive visual objects as unified entities, despite the preferential encoding of their various visual features in separate cortical areas. A 'binding' process is assumed to be required for creating this unified percept, but the underlying neural mechanism and specific brain areas are poorly understood. We investigated 'feature-binding' across two feature dimensions, using a novel stimulus configuration, designed to disambiguate whether a given combination of color and motion direction is perceived as bound or unbound. In the "bound" condition, two behaviorally relevant features (color and motion) belong to the same object, while in the "unbound" condition they belong to different objects. We recorded local field potentials from the lateral prefrontal cortex (lPFC) in macaque monkeys that actively monitored the different stimulus configurations. Our data show a neural representation of visual feature binding especially in the 4-12 Hz frequency band and a transmission of binding information between different lPFC neural subpopulations. This information is linked to the animal's reaction time, suggesting a behavioral relevance of the binding information. Together, our results document the involvement of the prefrontal cortex, targeted by the dorsal and ventral visual streams, in binding visual features from different dimensions, in a process that includes a dynamic modulation of low frequency inter-regional communication.

Spike-phase coupling as an order parameter in a leaky integrate-and-fire model.

It is known that the leaky integrate-and-fire neural model shows a transition from irregular to synchronous firing by increasing the coupling between the neurons. However, a quantitative characterization of this order-disorder transition, that is, the determination of the order of transition and also the critical exponents in the case of continuous transition, is not entirely known. In this work, we consider a network of N excitatory neurons with local connections, residing on a square lattice with periodic boundary conditions. The cooperation between neurons K plays the role of the control parameter that generates criticality when the critical cooperation strength K_{c} is adopted. We introduce the population-averaged voltage (PAV) as a representative value of the network's cooperative activity. Then, we show that the coupling between the timing of spikes and the phase of temporal fluctuations of PAV defined as m resorts to identify a Kuramoto order parameter. By increasing K, we find a continuous transition from irregular spiking to a phase-locked state at the critical point K_{c}. We deploy the finite-size scaling analysis to calculate the critical exponents of this transition. To explore the formal indicator of criticality, we study the neuronal avalanches profile at this critical point and find a scaling behavior with the exponents in a fair agreement with the experimental values both in vivo and in vitro.

Attention strengthens across-trial pre-stimulus phase coherence in visual cortex, enhancing stimulus processing.

Attention selectively routes the most behaviorally relevant information from the stream of sensory inputs through the hierarchy of cortical areas. Previous studies have shown that visual attention depends on the phase of oscillatory brain activities. These studies mainly focused on the stimulus presentation period, rather than the pre-stimulus period. Here, we hypothesize that selective attention controls the phase of oscillatory neural activities to efficiently process relevant information. We document an attentional modulation of pre-stimulus inter-trial phase coherence (a measure of deviation between instantaneous phases of trials) of low frequency local field potentials (LFP) in visual area MT of macaque monkeys. Our data reveal that phase coherence increases following a spatial cue deploying attention towards the receptive field of the recorded neural population. We further show that the attentional enhancement of phase coherence is positively correlated with the modulation of the stimulus-induced firing rate, and importantly, a higher phase coherence is associated with a faster behavioral response. These results suggest a functional utilization of intrinsic neural oscillatory activities for an enhanced processing of upcoming stimuli.

Routing information flow by separate neural synchrony frequencies allows for "functionally labeled lines" in higher primate cortex.

Efficient transfer of sensory information to higher (motor or associative) areas in primate visual cortical areas is crucial for transforming sensory input into behavioral actions. Dynamically increasing the level of coordination between single neurons has been suggested as an important contributor to this efficiency. We propose that differences between the functional coordination in different visual pathways might be used to unambiguously identify the source of input to the higher areas, ensuring a proper routing of the information flow. Here we determined the level of coordination between neurons in area MT in macaque visual cortex in a visual attention task via the strength of synchronization between the neurons' spike timing relative to the phase of oscillatory activities in local field potentials. In contrast to reports on the ventral visual pathway, we observed the synchrony of spikes only in the range of high gamma (180 to 220 Hz), rather than gamma (40 to 70 Hz) (as reported previously) to predict the animal's reaction speed. This supports a mechanistic role of the phase of high-gamma oscillatory activity in dynamically modulating the efficiency of neuronal information transfer. In addition, for inputs to higher cortical areas converging from the dorsal and ventral pathway, the distinct frequency bands of these inputs can be leveraged to preserve the identity of the input source. In this way source-specific oscillatory activity in primate cortex can serve to establish and maintain "functionally labeled lines" for dynamically adjusting cortical information transfer and multiplexing converging sensory signals.

Neural Activity Predicts Reaction in Primates Long Before a Behavioral Response.

How neural activity is linked to behavior is a critical question in neural engineering and cognitive neurosciences. It is crucial to predict behavior as early as possible, to plan a machine response in real-time brain computer interactions. However, previous studies have studied the neural readout of behavior only within a short time before the action is performed. This leaves unclear, if the neural activity long before a decision could predict the upcoming behavior. By recording extracellular neural activities from the visual cortex of behaving rhesus monkeys, we show that: (1) both, local field potentials (LFPs) and the rate of neural spikes long before (>2 s) a monkey responds to a change, foretell its behavioral performance in a spatially selective manner; (2) LFPs, the more accessible component of extracellular activity, are a stronger predictor of behavior; and (3) LFP amplitude is positively correlated while spiking activity is negatively correlated with behavioral reaction time (RT). These results suggest that field potentials could be used to predict behavior way before it is performed, an observation that could potentially be useful for brain computer interface applications, and that they contribute to the sensory neural circuit's speed in information processing.

Attention decouples action potentials from the phase of local field potentials in macaque visual cortical area MT.

BACKGROUND: The timing of action potentials ("spikes") of cortical neurons has been shown to be aligned to the phase of low-frequency (< 10 Hz) local field potentials (LFPs) in several cortical areas. However, across the areas, this alignment varies and the role of this spike-phase coupling (SPC) in cognitive functions is not well understood. RESULTS: Here, we propose a role in the coordination of neural activity by selective attention. After refining previous analytical methods for measuring SPC, we show that first, SPC is present along the dorsal processing pathway in macaque visual cortex (area MT); second, spikes occur in falling phases of the low-frequency LFP independent of the location of spatial attention; third, switching spatial attention into the receptive field (RF) of MT neurons decreases this coupling; and finally, the LFP phase causally influences the spikes. CONCLUSIONS: Here, we show that spikes are coupled to the phase of low-frequency LFP along the dorsal visual pathway. Our data suggest that attention harnesses this spike-LFP coupling to de-synchronize neurons and thereby enhance the neural representation of the attended stimuli.

Local field potentials are induced by visually evoked spiking activity in macaque cortical area MT.

Local field potentials (LFP) have been the focus of many recent studies in systems neuroscience. However, the exact neural basis of these signals remains unclear. To address this question, we determined the relationship between LFP signals and another, much better understood, signature of neural activity: action potentials. Specifically, we focused on the relationship between the amplitude of stimulus-induced LFPs and the magnitude of spiking activity in visual cortex of non-human primates. Our trial-by-trial correlation analyses between these two components of extracellular signals in macaque visual cortex show that the spike rate is coupled to the LFP amplitude with a surprisingly long latency, typically 50 ms. Our analysis shows that the neural spike rate is a significant predictor of the LFP amplitude. This limits the functional interpretation of LFP signals beyond that based on spiking activities.

Attention Decreases Phase-Amplitude Coupling, Enhancing Stimulus Discriminability in Cortical Area MT.

Local field potentials (LFPs) in cortex reflect synchronous fluctuations in the synaptic activity of local populations of neurons. The power of high frequency (>30 Hz) oscillations in LFPs is locked to the phase of low frequency (<30 Hz) oscillations, an effect known as phase-amplitude coupling (PAC). While PAC has been observed in a variety of cortical regions and animal models, its functional role particularly in primate visual cortex is largely unknown. Here, we document PAC for LFPs recorded from extra-striate area MT of macaque monkeys, an area specialized for the processing of visual motion. We further show that directing spatial attention into the receptive field of MT neurons decreases the coupling between the low frequency phase and high frequency power of LFPs. This attentional suppression of PAC increases neuronal discriminability for attended visual stimuli. Therefore, we hypothesize that visual cortex uses PAC to regulate inter-neuronal correlations and thereby enhances the coding of relevant stimuli.

Decoding of visual attention from LFP signals of macaque MT.

The local field potential (LFP) has recently been widely used in brain computer interfaces (BCI). Here we used power of LFP recorded from area MT of a macaque monkey to decode where the animal covertly attended. Support vector machines (SVM) were used to learn the pattern of power at different frequencies for attention to two possible positions. We found that LFP power at both low (<9 Hz) and high (31-120 Hz) frequencies contains sufficient information to decode the focus of attention. Highest decoding performance was found for gamma frequencies (31-120 Hz) and reached 82%. In contrast low frequencies (<9 Hz) could help the classifier reach a higher decoding performance with a smaller amount of training data. Consequently, we suggest that low frequency LFP can provide fast but coarse information regarding the focus of attention, while higher frequencies of the LFP deliver more accurate but less timely information about the focus of attention.