Beta oscillations in the monkey sensorimotor network reflect somatosensory decision making

Neurosystems: brain rhythms and cognitive processing

Neuronal rhythms are ubiquitous features of brain dynamics, and are highly correlated with cognitive processing. However, the relationship between the physiological mechanisms producing these rhythms and the functions associated with the rhythms remains mysterious. This article investigates the contributions of rhythms to basic cognitive computations (such as filtering signals by coherence and/or frequency) and to major cognitive functions (such as attention and multi-modal coordination). We offer support to the premise that the physiology underlying brain rhythms plays an essential role in how these rhythms facilitate some cognitive operations.

Decision-related pupil dilation reflects upcoming choice and individual bias

A number of studies have shown that pupil size increases transiently during effortful decisions. These decision-related changes in pupil size are mediated by central neuromodulatory systems, which also influence the internal state of brain regions engaged in decision making. It has been proposed that pupil-linked neuromodulatory systems are activated by the termination of decision processes, and, consequently, that these systems primarily affect the postdecisional brain state. Here, we present pupil results that run contrary to this proposal, suggesting an important intradecisional role. We measured pupil size while subjects formed protracted decisions about the presence or absence ("yes" vs. "no") of a visual contrast signal embedded in dynamic noise. Linear systems analysis revealed that the pupil was significantly driven by a sustained input throughout the course of the decision formation. This sustained component was larger than the transient component during the final choice (indicated by button press). The overall amplitude of pupil dilation during decision formation was bigger before yes than no choices, irrespective of the physical presence of the target signal. Remarkably, the magnitude of this pupil choice effect (yes > no) reflected the individual criterion: it was strongest in conservative subjects choosing yes against their bias. We conclude that the central neuromodulatory systems controlling pupil size are continuously engaged during decision formation in a way that reveals how the upcoming choice relates to the decision maker's attitude. Changes in brain state seem to interact with biased decision making in the face of uncertainty.

Coherent delta-band oscillations between cortical areas correlate with decision making

Coherent oscillations in the theta-to-gamma frequency range have been proposed as a mechanism that coordinates neural activity in large-scale cortical networks in sensory, motor, and cognitive tasks. Whether this mechanism also involves coherent oscillations at delta frequencies (1-4 Hz) is not known. Rather, delta oscillations have been associated with slow-wave sleep. Here, we show coherent oscillations in the delta frequency band between parietal and frontal cortices during the decision-making component of a somatosensory discrimination task. Importantly, the magnitude of this delta-band coherence is modulated by the different decision alternatives. Furthermore, during control conditions not requiring decision making, delta-band coherences are typically much reduced. Our work indicates an important role for synchronous activity in the delta frequency band when large-scale, distant cortical networks coordinate their neural activity during decision making.

A low-frequency oscillatory neural signal in humans encodes a developing decision variable

We often make decisions based on sensory evidence that is accumulated over a period of time. How the evidence for such decisions is represented in the brain and how such a neural representation is used to guide a subsequent action are questions of considerable interest to decision sciences. The neural correlates of developing perceptual decisions have been thoroughly investigated in the oculomotor system of macaques who communicated their decisions using an eye movement. It has been found that the evidence informing a decision to make an eye movement is in part accumulated within the same oculomotor circuits that signal the upcoming eye movement. Recent evidence suggests that the somatomotor system may exhibit an analogous property for choices made using a hand movement. To investigate this possibility, we engaged humans in a decision task in which they integrated discrete quanta of sensory information over a period of time and signaled their decision using a hand movement or an eye movement. The discrete form of the sensory evidence allowed us to infer the decision variable on which subjects base their decision on each trial and to assess the neural processes related to each quantum of the incoming decision evidence. We found that a low-frequency electrophysiological signal recorded over centroparietal regions strongly encodes the decision variable inferred in this task, and that it does so specifically for hand movement choices. The signal ramps up with a rate that is proportional to the decision variable, remains graded by the decision variable throughout the delay period, reaches a common peak shortly before a hand movement, and falls off shortly after the hand movement. Furthermore, the signal encodes the polarity of each evidence quantum, with a short latency, and retains the response level over time. Thus, this neural signal shows properties of evidence accumulation. These findings suggest that the decision-related effects observed in the oculomotor system of the monkey during eye movement choices may share the same basic properties with the decision-related effects in the somatomotor system of humans during hand movement choices.

Noise alters beta-band activity in superior temporal cortex during audiovisual speech processing

Speech recognition is improved when complementary visual information is available, especially under noisy acoustic conditions. Functional neuroimaging studies have suggested that the superior temporal sulcus (STS) plays an important role for this improvement. The spectrotemporal dynamics underlying audiovisual speech processing in the STS, and how these dynamics are affected by auditory noise, are not well understood. Using electroencephalography, we investigated how auditory noise affects audiovisual speech processing in event-related potentials (ERPs) and oscillatory activity. Spoken syllables were presented in audiovisual (AV) and auditory only (A) trials at three different auditory noise levels (no, low, and high). Responses to A stimuli were subtracted from responses to AV stimuli, separately for each noise level, and these responses were subjected to the statistical analysis. Central ERPs differed between the no noise and the two noise conditions from 130 to 150 ms and 170 to 210 ms after auditory stimulus onset. Source localization using the local autoregressive average procedure revealed an involvement of the lateral temporal lobe, encompassing the superior and middle temporal gyrus. Neuronal activity in the beta-band (16 to 32 Hz) was suppressed at central channels around 100 to 400 ms after auditory stimulus onset in the averaged AV minus A signal over the three noise levels. This suppression was smaller in the high noise compared to the no noise and low noise condition, possibly reflecting disturbed recognition or altered processing of multisensory speech stimuli. Source analysis of the beta-band effect using linear beamforming demonstrated an involvement of the STS. Our study shows that auditory noise alters audiovisual speech processing in ERPs localized to lateral temporal lobe and provides evidence that beta-band activity in the STS plays a role for audiovisual speech processing under regular and noisy acoustic conditions.

Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks

Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks.

How is the functional role of a particular neuron established within an ensemble? The concept of a neural tuning curve – the mapping from input variables such as movement direction to output firing rate – has proven useful in investigating neural function. However, prior work shows that tuning curves are not fixed but may be remapped as a function of task demands – presumably via high-level mechanisms of cognitive control. How is this accomplished? Brain rhythms may play a causal role in this process, but the coupling of single cells to network activity remains poorly understood. We investigated the coupling between rhythmic beta activity and spiking as macaques performed two different tasks. This coupling can be described in terms of a function that maps oscillatory amplitude and phase to instantaneous spike rate. Similarly to direction tuning, this “internal” tuning curve also exhibits task-dependent changes. We characterize these changes across a large ensemble of simultaneously-recorded cells, and consider some of the neuro-computational implications presented by cross-level coupling between single cells and large-scale networks. In particular, relative to the slow time-scale of behavior, the observed beta-to-rate mappings may prove useful for modulating winner-take-all dynamics on intermediate time-scales and relative spike timing on fast time-scales.

Interactions between visual and motor areas during the recognition of plausible actions as revealed by magnetoencephalography

Several studies have shown activation of the mirror neuron system (MNS), comprising the temporal, posterior parietal, and sensorimotor areas when observing plausible actions, but far less is known on how these cortical areas interact during the recognition of a plausible action. Here, we recorded neural activity with magnetoencephalography while subjects viewed point-light displays of biologically plausible and scrambled versions of actions. We were interested in modulations of oscillatory activity and, specifically, in coupling of oscillatory activity between visual and motor areas. Both plausible and scrambled actions elicited modulations of θ (5-7 Hz), α (7-13 Hz), β (13-35 Hz), and γ (55-100 Hz) power within visual and motor areas. When comparing between the two actions, we observed sequential and spatially distinct increases of γ (∼65 Hz), β (∼25 Hz), and α (∼11 Hz) power between 0.5 and 1.3 s in parieto-occipital, sensorimotor, and left temporal areas. In addition, significant clusters of γ (∼65 Hz) and α/β (∼15 Hz) power decrease were observed in right temporal and parieto-occipital areas between 1.3 and 2.0 s. We found β-power in sensorimotor areas to be positively correlated on a trial-by-trial basis with parieto-occipital γ and left temporal α-power for the plausible but not for the scrambled condition. These results provide new insights in the neuronal oscillatory activity of the areas involved in the recognition of plausible action movements and their interaction. The power correlations between specific areas underscore the importance of interactions between visual and motor areas of the MNS during the recognition of a plausible action.

The ups and downs of β oscillations in sensorimotor cortex

Since the first descriptions of sensorimotor rhythms by Berger (1929) and by Jasper and Penfield (1949), the potential role of beta oscillations (~13-30 Hz) in the brain has been intensely investigated. We start this review by showing that experimental studies in humans and monkeys have reached a consensus on the facts that sensorimotor beta power is low during movement, transiently increases after movement end (the "beta rebound") and tonically increases during object grasping. Recently, a new surge of studies exploiting more complex sensorimotor tasks including multiple events, such as instructed delay tasks, reveal novel characteristics of beta oscillatory activity. We therefore proceed by critically reviewing also this literature to understand whether modulations of beta oscillations in task epochs other than those during and after movement are consistent across studies, and whether they can be reconciled with a role for beta oscillations in sensorimotor transmission. We indeed find that there are additional processes that also strongly affect sensorimotor beta oscillations, such as visual cue anticipation and processing, fitting with the view that beta oscillations reflect heightened sensorimotor transmission beyond somatosensation. However, there are differences among studies, which may be interpreted more readily if we assume multiple processes, whose effects on the overall measured beta power overlap in time. We conclude that beta oscillations observed in sensorimotor cortex may serve large-scale communication between sensorimotor and other areas and the periphery.

Conversion of sensory signals into perceptual decisions

A fundamental problem in neurobiology is to understand how brain circuits represent sensory information and how such representations give rise to perception, memory and decision-making. We demonstrate that a sensory stimulus engages multiple areas of the cerebral cortex, including primary sensory, prefrontal, premotor and motor cortices. As information transverses the cortical circuits it shows progressively more relation to perception, memory and decision reports. In particular, we show how somatosensory areas on the parietal lobe generate a parameterized representation of a tactile stimulus. This representation is maintained in working memory by prefrontal and premotor areas of the frontal lobe. The presentation of a second stimulus, that monkeys are trained to compare with the first, generates decision-related activity reflecting which stimulus had the higher frequency. Importantly, decision-related activity is observed across several cortical circuits including prefrontal, premotor and parietal cortices. Sensory information is encoded by neuronal populations with opposite tuning, and suggests that a simple subtraction operation could be the underlying mechanism by which past and present sensory information is compared to generate perceptual decisions.

Somatosensory Anticipatory Alpha Activity Increases to Suppress Distracting Input

Effective processing of sensory input in daily life requires attentional selection and amplification of relevant input and, just as importantly, attenuation of irrelevant information. It has been proposed that top–down modulation of oscillatory alpha band activity (8–14 Hz) serves to allocate resources to various regions, depending on task demands. In previous work, we showed that contralateral somatosensory alpha activity decreases to facilitate processing of an anticipated target stimulus in a tactile discrimination task. In the current study, we asked whether somatosensory alpha activity is also modulated when expecting incoming distracting stimuli on the nonattended side. We hypothesized that an ipsilateral increase of alpha to suppress distracters would be required for optimal task performance. We recorded magneto-encephalography while subjects performed a tactile stimulus discrimination task where a cue directed attention either to their left or right hand. Distracters were presented simultaneously to the unattended hand. We found that alpha power contralateral to the attended hand decreased, whereas ipsilateral alpha power increased. In addition, posterior alpha power showed a general increase. Importantly, these three alpha components all contributed to discrimination performance. This study further extends the notion that alpha band activity is involved in shaping the functional architecture of the working brain by determining the engagement and disengagement of specific regions: Contralateral alpha decreases to facilitate stimulus detection, whereas ipsilateral alpha increases when active suppression of distracters is required. Importantly, the ipsilateral alpha increase is crucial for optimal task performance.

Spectral fingerprints of large-scale neuronal interactions

Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.