Gamma synchrony predicts neuron-neuron correlations and correlations with motor behavior in extrastriate visual area MT

Coupled oscillations orchestrate selective information transmission in visual cortex

Performing visually guided behavior involves flexible routing of sensory information towards associative areas. We hypothesize that in visual cortical areas, this routing is shaped by a gating influence of the local neuronal population on the activity of the same population's single neurons. We analyzed beta frequencies (representing local population activity), high-gamma frequencies (representative of the activity of local clusters of neurons), and the firing of single neurons in the medial temporal (MT) area of behaving rhesus monkeys. Our results show an influence of beta activity on single neurons, predictive of behavioral performance. Similarly, the temporal dependence of high-gamma on beta predicts behavioral performance. These demonstrate a unidirectional influence of network-level neural dynamics on single-neuron activity, preferentially routing relevant information. This demonstration of a local top-down influence unveils a previously unexplored perspective onto a core feature of cortical information processing: the selective transmission of sensory information to downstream areas based on behavioral relevance.

Sensorimotor-linked reward modulates smooth pursuit eye movements in monkeys

Reward is essential for shaping behavior. Using sensory cues to imply forthcoming rewards, previous studies have demonstrated powerful effects of rewards on behavior. Nevertheless, the impact of reward on the sensorimotor transformation, particularly when reward is linked to behavior remains uncertain. In this study, we investigated how reward modulates smooth pursuit eye movements in monkeys. Three distinct associations between reward and eye movements were conducted in independent blocks. Results indicated that reward increased eye velocity during the steady-state pursuit, rather than during the initiation. The influence depended on the particular association between behavior and reward: a faster eye velocity was linked with reward. Neither rewarding slower eye movements nor randomizing rewards had a significant effect on behavior. The findings support the existence of distinct mechanisms involved in the initiation and steady-state phases of pursuit, and contribute to a deeper understanding of how reward interacts with these two periods of pursuit.

Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations

Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.

Prior expectation enhances sensorimotor behavior by modulating population tuning and subspace activity in sensory cortex

Prior knowledge facilitates our perception and goal-directed behaviors, particularly when sensory input is lacking or noisy. However, the neural mechanisms underlying the improvement in sensorimotor behavior by prior expectations remain unknown. In this study, we examine the neural activity in the middle temporal (MT) area of visual cortex while monkeys perform a smooth pursuit eye movement task with prior expectation of the visual target's motion direction. Prior expectations discriminately reduce the MT neural responses depending on their preferred directions, when the sensory evidence is weak. This response reduction effectively sharpens neural population direction tuning. Simulations with a realistic MT population demonstrate that sharpening the tuning can explain the biases and variabilities in smooth pursuit, suggesting that neural computations in the sensory area alone can underpin the integration of prior knowledge and sensory evidence. State-space analysis further supports this by revealing neural signals of prior expectations in the MT population activity that correlate with behavioral changes.

Frontal-to-visual information flow explains predictive motion tracking

Predictive tracking demonstrates our ability to maintain a line of vision on moving objects even when they temporarily disappear. Models of smooth pursuit eye movements posit that our brain achieves this ability by directly streamlining motor programming from continuously updated sensory motion information. To test this hypothesis, we obtained sensory motion representation from multivariate electroencephalogram activity while human participants covertly tracked a temporarily occluded moving stimulus with their eyes remaining stationary at the fixation point. The sensory motion representation of the occluded target evolves to its maximum strength at the expected timing of reappearance, suggesting a timely modulation of the internal model of the visual target. We further characterize the spatiotemporal dynamics of the task-relevant motion information by computing the phase gradients of slow oscillations. We discovered a predominant posterior-to-anterior phase gradient immediately after stimulus occlusion; however, at the expected timing of reappearance, the axis reverses the gradient, becoming anterior-to-posterior. The behavioral bias of smooth pursuit eye movements, which is a signature of the predictive process of the pursuit, was correlated with the posterior division of the gradient. These results suggest that the sensory motion area modulated by the prediction signal is involved in updating motor programming.

The effect of temporal expectation on the correlations of frontal neural activity with alpha oscillation and sensory-motor latency

In a dynamic environment, we seek to enhance behavioral responses by anticipating future events. Previous studies have shown that the probability distribution of the timing of future events could shape our expectation of event timing; furthermore, the modulation of alpha oscillation is known to be a critical neural factor. However, a link between the modulation of alpha oscillation by temporal expectation and single neural activity is missing. In this study, we investigated how temporal expectation modulated frontal neural activities and behavioral reaction time by recording neural activity from the frontal eye field smooth pursuit eye movement region of monkeys while they performed a smooth pursuit eye movement task. We found that the temporal expectation reduced the coherence between the neural spiking and alpha frequency of the local field potential, along with the trial-by-trial correlation between the neural spiking activity and pursuit latency. This result suggests that the desynchronization of alpha oscillation by temporal expectation would be related to the decorrelation of population neural activity, which could be the neural source of reaction time enhancement by temporal expectation.

Differential Recovery of Submodality Touch Neurons and Interareal Communication in Sensory Input-Deprived Area 3b and S2 Cortices

Cortical reactivation and regain of interareal functional connections have been linked to the recovery of hand grasping behavior after loss of sensory inputs in primates. We investigated contributions of neurons in two hierarchically organized somatosensory areas, 3b and S2, by characterizing local field potential (LFP) and multiunit spiking activity in five states (rest, stimulus-on, sustained, stimulus-off, and induced) and interareal communication after grasping behavior of dorsal column lesioned male squirrel monkeys had mostly recovered. Compared with normal cortex, fMRI, LFP, and spiking response magnitudes to step indentations were significantly weaker. The sustained component of the spiking recovered much better than the stimulus-off response. Correlation between overall spiking and γ LFP remained strong within each recovered areas 3b and S2. The interareal correlations of γ LFP were severely disrupted, except in the resting and stimulus-on periods. Interareal correlation of spiking was disrupted in the stimulus-off period only. In summary, submodality of low threshold mechanoreceptive neurons recovered differentially in input-deprived area 3b and S2 when impaired global hand grasping behavior returned. Slow-adapting-like neurons recovered, whereas rapid-adapting-like neurons did not. Interareal communications were also severely compromised. We propose that slow-adapting-like neurons and afferents in recovered area 3b and S2 mediate recovery of impaired grasping behavior after dorsal column tract lesion.SIGNIFICANCE STATEMENT Sensory feedback is essential for execution of hand grasping behavior in primates. Reactivations of somatosensory cortices have been attributed to recovery of such behavior after loss of sensory inputs via largely unknown mechanisms. In input-deprived area 3b and S2 cortex, after hand grasping behavior mostly recovered, we found slow-adapting-like neurons were greatly recovered, whereas rapid-adapting-like neurons did not. Communications between area 3b and S2 neurons were severely compromised. We suggest that recovery of slow-adapting-like neurons in input-deprived area 3b and S2 may mediate the recovery of hand grasping behavior.

Decision Signals in the Local Field Potentials of Early and Mid-Level Macaque Visual Cortex

The neural basis of perceptual decision making has typically been studied using measurements of single neuron activity, though decisions are likely based on the activity of large neuronal ensembles. Local field potentials (LFPs) may, in some cases, serve as a useful proxy for population activity and thus be useful for understanding the neural basis of perceptual decision making. However, little is known about whether LFPs in sensory areas include decision-related signals. We therefore analyzed LFPs recorded using two 48-electrode arrays implanted in primary visual cortex (V1) and area V4 of macaque monkeys trained to perform a fine orientation discrimination task. We found significant choice information in low (0-30 Hz) and higher (70-500 Hz) frequency components of the LFP, but little information in gamma frequencies (30-70 Hz). Choice information was more robust in V4 than V1 and stronger in LFPs than in simultaneously measured spiking activity. LFP-based choice information included a global component, common across electrodes within an area. Our findings reveal the presence of robust choice-related signals in the LFPs recorded in V1 and V4 and suggest that LFPs may be a useful complement to spike-based analyses of decision making.

The Neural Basis for Response Latency in a Sensory-Motor Behavior

We seek a neural circuit explanation for sensory-motor reaction times. In the smooth eye movement region of the frontal eye fields (FEFSEM), the latencies of pairs of neurons show trial-by-trial correlations that cause trial-by-trial correlations in neural and behavioral latency. These correlations can account for two-third of the observed variation in behavioral latency. The amplitude of preparatory activity also could contribute, but the responses of many FEFSEM neurons fail to support predictions of the traditional "ramp-to-threshold" model. As a correlate of neural processing that determines reaction time, the local field potential in FEFSEM includes a brief wave in the 5-15-Hz frequency range that precedes pursuit initiation and whose phase is correlated with the latency of pursuit in individual trials. We suggest that the latency of the incoming visual motion signals combines with the state of preparatory activity to determine the latency of the transient response that controls eye movement.

IMPACT STATEMENT

The motor cortex for smooth pursuit eye movements contributes to sensory-motor reaction time through the amplitude of preparatory activity and the latency of transient, visually driven responses.

Effect of Prior Direction Expectation on the Accuracy and Precision of Smooth Pursuit Eye Movements

The integration of sensory with top–down cognitive signals for generating appropriate sensory–motor behaviors is an important issue in understanding the brain’s information processes. Recent studies have demonstrated that the interplay between sensory and high-level signals in oculomotor behavior could be explained by Bayesian inference. Specifically, prior knowledge for motion speed introduces a bias in the speed of smooth pursuit eye movements. The other important prediction of Bayesian inference is variability reduction by prior expectation; however, there is insufficient evidence in oculomotor behaviors to support this prediction. In the present study, we trained monkeys to switch the prior expectation about motion direction and independently controlled the strength of the motion stimulus. Under identical sensory stimulus conditions, we tested if prior knowledge about the motion direction reduced the variability of open-loop smooth pursuit eye movements. We observed a significant reduction when the prior expectation was strong; this was consistent with the prediction of Bayesian inference. Taking advantage of the open-loop smooth pursuit, we investigated the temporal dynamics of the effect of the prior to the pursuit direction bias and variability. This analysis demonstrated that the strength of the sensory evidence depended not only on the strength of the sensory stimulus but also on the time required for the pursuit system to form a neural sensory representation. Finally, we demonstrated that the variability and directional bias change by prior knowledge were quantitatively explained by the Bayesian observer model.

Motion direction representation in multivariate electroencephalography activity for smooth pursuit eye movements

Visually-guided smooth pursuit eye movements are composed of initial open-loop and later steady-state periods. Feedforward sensory information dominates the motor behavior during the open-loop pursuit, and a more complex feedback loop regulates the steady-state pursuit. To understand the neural representations of motion direction during open-loop and steady-state smooth pursuits, we recorded electroencephalography (EEG) responses from human observers while they tracked random-dot kinematograms as pursuit targets. We estimated population direction tuning curves from multivariate EEG activity using an inverted encoding model. We found significant direction tuning curves as early as about 60 ms from stimulus onset. Direction tuning responses were generalized to later times during the open-loop smooth pursuit, but they became more dynamic during the later steady-state pursuit. The encoding quality of retinal motion direction information estimated from the early direction tuning curves was predictive of trial-by-trial variation in initial pursuit directions. These results suggest that the movement directions of open-loop smooth pursuit are guided by the representation of the retinal motion present in the multivariate EEG activity.

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

Dynamical coordination of the neural activity between individual neurons is known to have a key role in the efficient transfer of sensory information to associative areas. Here, we report a role of interneuronal synchrony within the high-gamma (180 to 220 Hz) frequency range of activity in macaque area MT (a visual area in the dorsal visual pathway) in determining behavioral performance. This is, however, in contrast to previous reports for the ventral visual pathway (such as area V4), where only gamma range (40 to 70 Hz) was observed to play a role. We propose that such a difference between the functional coordination in different visual pathways might be used to unambiguously identify the source of input to the higher areas.

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.

Dissecting patterns of preparatory activity in the frontal eye fields during pursuit target selection

We investigated the composition of preparatory activity of frontal eye field (FEF) neurons in monkeys performing a pursuit target selection task. In response to the orthogonal motion of a large and a small reward target, monkeys initiated pursuit biased toward the direction of large reward target motion. FEF neurons exhibited robust preparatory activity preceding movement initiation in this task. Preparatory activity consisted of two components, ramping activity that was constant across target selection conditions, and a flat offset in firing rates that signaled the target selection condition. Ramping activity accounted for 50% of the variance in the preparatory activity and was linked most strongly, on a trial-by-trial basis, to pursuit eye movement latency rather than to its direction or gain. The offset in firing rates that discriminated target selection conditions accounted for 25% of the variance in the preparatory activity and was commensurate with a winner-take-all representation, signaling the direction of large reward target motion rather than a representation that matched the parameters of the upcoming movement. These offer new insights into the role that the frontal eye fields play in target selection and pursuit control. They show that preparatory activity in the FEF signals more strongly when to move rather than where or how to move and suggest that structures outside the FEF augment its contributions to the target selection process.NEW & NOTEWORTHY We used the smooth eye movement pursuit system to link between patterns of preparatory activity in the frontal eye fields and movement during a target selection task. The dominant pattern was a ramping signal that did not discriminate between selection conditions and was linked, on trial-by-trial basis, to movement latency. A weaker pattern was composed of a constant signal that discriminated between selection conditions but was only weakly linked to the movement parameters.

Responses of Purkinje cells in the oculomotor vermis of monkeys during smooth pursuit eye movements and saccades: comparison with floccular complex

We recorded the responses of Purkinje cells in the oculomotor vermis during smooth pursuit and saccadic eye movements. Our goal was to characterize the responses in the vermis using approaches that would allow direct comparisons with responses of Purkinje cells in another cerebellar area for pursuit, the floccular complex. Simple-spike firing of vermis Purkinje cells is direction selective during both pursuit and saccades, but the preferred directions are sufficiently independent so that downstream circuits could decode signals to drive pursuit and saccades separately. Complex spikes also were direction selective during pursuit, and almost all Purkinje cells showed a peak in the probability of complex spikes during the initiation of pursuit in at least one direction. Unlike the floccular complex, the preferred directions for simple spikes and complex spikes were not opposite. The kinematics of smooth eye movement described the simple-spike responses of vermis Purkinje cells well. Sensitivities were similar to those in the floccular complex for eye position and considerably lower for eye velocity and acceleration. The kinematic relations were quite different for saccades vs. pursuit, supporting the idea that the contributions from the vermis to each kind of movement could contribute independently in downstream areas. Finally, neither the complex-spike nor the simple-spike responses of vermis Purkinje cells were appropriate to support direction learning in pursuit. Complex spikes were not triggered reliably by an instructive change in target direction; simple-spike responses showed very small amounts of learning. We conclude that the vermis plays a different role in pursuit eye movements compared with the floccular complex.NEW & NOTEWORTHY The midline oculomotor cerebellum plays a different role in smooth pursuit eye movements compared with the lateral, floccular complex and appears to be much less involved in direction learning in pursuit. The output from the oculomotor vermis during pursuit lies along a null-axis for saccades and vice versa. Thus the vermis can play independent roles in the two kinds of eye movement.

Functional states of rat cortical circuits during the unpredictable availability of a reward-related cue

Proper performance of acquired abilities can be disturbed by the unexpected occurrence of external changes. Rats trained with an operant conditioning task (to press a lever in order to obtain a food pellet) using a fixed-ratio (1:1) schedule were subsequently placed in a Skinner box in which the lever could be removed randomly. Field postsynaptic potentials (fPSPs) were chronically evoked in perforant pathway-hippocampal CA1 (PP-CA1), CA1-subiculum (CA1-SUB), CA1-medial prefrontal cortex (CA1-mPFC), mPFC-nucleus accumbens (mPFC-NAc), and mPFC-basolateral amygdala (mPFC-BLA) synapses during lever IN and lever OUT situations. While lever presses were accompanied by a significant increase in fPSP slopes at the five synapses, the unpredictable absence of the lever were accompanied by decreased fPSP slopes in all, except PP-CA1 synapses. Spectral analysis of local field potentials (LFPs) recorded when the animal approached the corresponding area in the lever OUT situation presented lower spectral powers than during lever IN occasions for all recording sites, apart from CA1. Thus, the unpredictable availability of a reward-related cue modified the activity of cortical and subcortical areas related with the acquisition of operant learning tasks, suggesting an immediate functional reorganization of these neural circuits to address the changed situation and to modify ongoing behaviors accordingly.

Signal, Noise, and Variation in Neural and Sensory-Motor Latency

Analysis of the neural code for sensory-motor latency in smooth pursuit eye movements reveals general principles of neural variation and the specific origin of motor latency. The trial-by-trial variation in neural latency in MT comprises a shared component expressed as neuron-neuron latency correlations and an independent component that is local to each neuron. The independent component arises heavily from fluctuations in the underlying probability of spiking, with an unexpectedly small contribution from the stochastic nature of spiking itself. The shared component causes the latency of single-neuron responses in MT to be weakly predictive of the behavioral latency of pursuit. Neural latency deeper in the motor system is more strongly predictive of behavioral latency. A model reproduces both the variance of behavioral latency and the neuron-behavior latency correlations in MT if it includes realistic neural latency variation, neuron-neuron latency correlations in MT, and noisy gain control downstream of MT.

Tinnitus: animal models and findings in humans

Chronic tinnitus (ringing of the ears) is a medically untreatable condition that reduces quality of life for millions of individuals worldwide. Most cases are associated with hearing loss that may be detected by the audiogram or by more sensitive measures. Converging evidence from animal models and studies of human tinnitus sufferers indicates that, while cochlear damage is a trigger, most cases of tinnitus are not generated by irritative processes persisting in the cochlea but by changes that take place in central auditory pathways when auditory neurons lose their input from the ear. Forms of neural plasticity underlie these neural changes, which include increased spontaneous activity and neural gain in deafferented central auditory structures, increased synchronous activity in these structures, alterations in the tonotopic organization of auditory cortex, and changes in network behavior in nonauditory brain regions detected by functional imaging of individuals with tinnitus and corroborated by animal investigations. Research on the molecular mechanisms that underlie neural changes in tinnitus is in its infancy and represents a frontier for investigation.

Smooth pursuit preparation modulates neuronal responses in visual areas MT and MST

Primates are able to track small moving visual targets using smooth pursuit eye movements. Target motion for smooth pursuit is signaled by neurons in visual cortical areas MT and MST. In this study, we trained monkeys to either initiate or withhold smooth pursuit in the presence of a moving target to test whether this decision was reflected in the relative strength of "go" and "no-go" processes. We found that the gain of the motor response depended strongly on whether monkeys were instructed to initiate or withhold pursuit, thus demonstrating voluntary control of pursuit initiation. We found that the amplitude of the neuronal response to moving targets in areas MT and MST was also significantly lower on no-go trials (by 2.1 spikes/s on average). The magnitude of the neural response reduction was small compared with the behavioral gain reduction. There were no significant differences in neuronal direction selectivity, spatial selectivity, or response reliability related to pursuit initiation or the absence thereof. Variability in eye speed was negatively correlated with firing rate variability after target motion onset during go trials but not during no-go trials, suggesting that MT and MST activity represents an error signal for a negative feedback controller. We speculate that modulation of the visual motion signals in areas MT and MST may be one of the first visual cortical events in the initiation of smooth pursuit and that the small early response modulation may be amplified to produce an all-or-none motor response by downstream areas.

How and why neural and motor variation are related

Movements are variable. Recent findings in smooth pursuit eye movements provide an explanation for motor variation in terms of the organization of the brain's sensory-motor pathways. Variation in sensory estimation is propagated through sensory-motor circuits and ultimately causes motor variation. The sensory origin of motor variation creates trial-by-trial correlations among the responses of neurons at each level of the sensory motor circuit, and between neural and behavioral responses. We suggest that motor variation is a compromise between multiple competing constraints. The brain strives for motor behavior that is 'good enough' in the face of constraints that tend to promote variation.

Detecting pairwise correlations in spike trains: an objective comparison of methods and application to the study of retinal waves

Correlations in neuronal spike times are thought to be key to processing in many neural systems. Many measures have been proposed to summarize these correlations and of these the correlation index is widely used and is the standard in studies of spontaneous retinal activity. We show that this measure has two undesirable properties: it is unbounded above and confounded by firing rate. We list properties needed for a measure to fairly quantify and compare correlations and we propose a novel measure of correlation-the spike time tiling coefficient. This coefficient, the correlation index, and 33 other measures of correlation of spike times are blindly tested for the required properties on synthetic and experimental data. Based on this, we propose a measure (the spike time tiling coefficient) to replace the correlation index. To demonstrate the benefits of this measure, we reanalyze data from seven key studies, which previously used the correlation index to investigate the nature of spontaneous activity. We reanalyze data from β2(KO) and β2(TG) mutants, mutants lacking connexin isoforms, and also the age-dependent changes in wild-type and β2(KO) correlations. Reanalysis of the data using the proposed measure can significantly change the conclusions. It leads to better quantification of correlations and therefore better inference from the data. We hope that the proposed measure will have wide applications, and will help clarify the role of activity in retinotopic map formation.

The Neural Code for Motor Control in the Cerebellum and Oculomotor Brainstem

Our paper evaluates the nature of the neural code under conditions where we can understand the details of trial-by-trial neural variation and its relationship to behavior. We demonstrate that a single extra spike in the activity of a neuron can predict impending motor behavior.

Spike trains are rich in information that can be extracted to guide behaviors at millisecond time resolution or across longer time intervals. In sensory systems, the information usually is defined with respect to the stimulus. Especially in motor systems, however, it is equally critical to understand how spike trains predict behavior. Thus, our goal was to compare systematically spike trains in the oculomotor system with eye movement behavior on single movements. We analyzed the discharge of Purkinje cells in the floccular complex of the cerebellum, floccular target neurons in the brainstem, other vestibular neurons, and abducens neurons. We find that an extra spike in a brief analysis window predicts a substantial fraction of the trial-by-trial variation in the initiation of smooth pursuit eye movements. For Purkinje cells, a single extra spike in a 40 ms analysis window predicts, on average, 0.5 SDs of the variation in behavior. An optimal linear estimator predicts behavioral variation slightly better than do spike counts in brief windows. Simulations reveal that the ability of single spikes to predict a fraction of behavior also emerges from model spike trains that have the same statistics as the real spike trains, as long as they are driven by shared sensory inputs. We think that the shared sensory estimates in their inputs create correlations in neural spiking across time and across each population. As a result, one or a small number of spikes in a brief time interval can predict a substantial fraction of behavioral variation.