Attentional selection and communication through coherence: Scope and limitations.

Synchronous neural oscillations are strongly associated with a variety of perceptual, cognitive, and behavioural processes. It has been proposed that the role of the synchronous oscillations in these processes is to facilitate information transmission between brain areas, the 'communication through coherence,' or CTC hypothesis. The details of how this mechanism would work, however, and its causal status, are still unclear. Here we investigate computationally a proposed mechanism for selective attention that directly implicates the CTC as causal. The mechanism involves alpha band (about 10 Hz) oscillations, originating in the pulvinar nucleus of the thalamus, being sent to communicating cortical areas, organizing gamma (about 40 Hz) oscillations there, and thus facilitating phase coherence and communication between them. This is proposed to happen contingent on control signals sent from higher-level cortical areas to the thalamic reticular nucleus, which controls the alpha oscillations sent to cortex by the pulvinar. We studied the scope of this mechanism in parameter space, and limitations implied by this scope, using a computational implementation of our conceptual model. Our results indicate that, although the CTC-based mechanism can account for some effects of top-down and bottom-up attentional selection, its limitations indicate that an alternative mechanism, in which oscillatory coherence is caused by communication between brain areas rather than being a causal factor for it, might operate in addition to, or even instead of, the CTC mechanism.

Top-down alpha oscillatory network interactions during visuospatial attention orienting.

Neuroimaging and lesion studies indicate that visual attention is controlled by a distributed network of brain areas. The covert control of visuospatial attention has also been associated with retinotopic modulation of alpha-band oscillations within early visual cortex, which are thought to underlie inhibition of ignored areas of visual space. The relation between distributed networks mediating attention control and more focal oscillatory mechanisms, however, remains unclear. The present study evaluated the hypothesis that alpha-band, directed, network interactions within the attention control network are systematically modulated by the locus of visuospatial attention. We localized brain areas involved in visuospatial attention orienting using magnetoencephalographic (MEG) imaging and investigated alpha-band Granger-causal interactions among activated regions using narrow-band transfer entropy. The deployment of attention to one side of visual space was indexed by lateralization of alpha power changes between about 400ms and 700ms post-cue onset. The changes in alpha power were associated, in the same time period, with lateralization of anterior-to-posterior information flow in the alpha-band from various brain areas involved in attention control, including the anterior cingulate cortex, left middle and inferior frontal gyri, left superior temporal gyrus, and right insula, and inferior parietal lobule, to early visual areas. We interpreted these results to indicate that distributed network interactions mediated by alpha oscillations exert top-down influences on early visual cortex to modulate inhibition of processing for ignored areas of visual space.

The benefits of noise in neural systems: bridging theory and experiment.

Although typically assumed to degrade performance, random fluctuations, or noise, can sometimes improve information processing in non-linear systems. One such form of 'stochastic facilitation', stochastic resonance, has been observed to enhance processing both in theoretical models of neural systems and in experimental neuroscience. However, the two approaches have yet to be fully reconciled. Understanding the diverse roles of noise in neural computation will require the design of experiments based on new theory and models, into which biologically appropriate experimental detail feeds back at various levels of abstraction.

An "ecological" action-based synthesis.

We expand upon Morsella et al.'s synthesis in the direction of what Gibson (1979) called an ecological approach to perception. Morsella et al. describe consciousness as a director of voluntary action, but they understate the role of the environment in its evolution as well as in directing behavior. We elaborate these roles in the context of the concept of affordances.

Dynamics of gamma bursts in local field potentials.

In this letter, we provide a stochastic analysis of, and supporting simulation data for, a stochastic model of the generation of gamma bursts in local field potential (LFP) recordings by interacting populations of excitatory and inhibitory neurons. Our interest is in behavior near a fixed point of the stochastic dynamics of the model. We apply a recent limit theorem of stochastic dynamics to probe into details of this local behavior, obtaining several new results. We show that the stochastic model can be written in terms of a rotation multiplied by a two-dimensional standard Ornstein-Uhlenbeck (OU) process. Viewing the rewritten process in terms of phase and amplitude processes, we are able to proceed further in analysis. We demonstrate that gamma bursts arise in the model as excursions of the modulus of the OU process. The associated pair of stochastic phase and amplitude processes satisfies their own pair of stochastic differential equations, which indicates that large phase slips occur between gamma bursts. This behavior is mirrored in LFP data simulated from the original model. These results suggest that the rewritten model is a valid representation of the behavior near the fixed point for a wide class of models of oscillatory neural processes.

A review of methods for identifying stochastic resonance in simulations of single neuron models.

Stochastic resonance (SR) is said to be observed when the presence of noise in a nonlinear system enables an output signal from the system to better represent some feature of an input signal than it does in the absence of noise. The effect has been observed in models of individual neurons, and in experiments performed on real neural systems. Despite the ubiquity of biophysical sources of stochastic noise in the nervous system, however, it has not yet been established whether neuronal computation mechanisms involved in performance of specific functions such as perception or learning might exploit such noise as an integral component, such that removal of the noise would diminish performance of these functions. In this paper we revisit the methods used to demonstrate stochastic resonance in models of single neurons. This includes a previously unreported observation in a multicompartmental model of a CA1-pyramidal cell. We also discuss, as a contrast to these classical studies, a form of 'stochastic facilitation', known as inverse stochastic resonance. We draw on the reviewed examples to argue why new approaches to studying 'stochastic facilitation' in neural systems need to be developed.

Stochastic resonance in the sensory systems and its applications in neural prosthetics.

Noise is generally considered to be detrimental. In the right conditions, however, noise can improve signal detection or information transmission. This counterintuitive phenomenon is called stochastic resonance (SR). SR has generated significant interdisciplinary interest, particularly in physics, engineering, and medical and environmental sciences. In this review, we discuss a growing empirical literature that suggests that noise at the right intensity may improve the detection and processing of auditory, sensorimotor, and visual stimuli. We focus particularly on applications of SR in sensory biology and investigate whether SR-based technologies present a pathway to improve outcomes for individuals living with sensory impairments. We conclude that there is considerable evidence supporting the application of SR in developing sensory prosthetics. However, the progression of SR-based technologies is variable across the sensory modalities. We suggest opportunities for further advancements in each modality, considering the best approaches to maximise benefits and capitalise on progress already made. Overall, SR can offer opportunities to improve existing technologies or to motivate innovations.

Does stochastic resonance improve performance for individuals with higher autism-spectrum quotient?

While noise is generally believed to impair performance, the detection of weak stimuli can sometimes be enhanced by introducing optimum noise levels. This phenomenon is termed 'Stochastic Resonance' (SR). Past evidence suggests that autistic individuals exhibit higher neural noise than neurotypical individuals. It has been proposed that the enhanced performance in Autism Spectrum Disorder (ASD) on some tasks could be due to SR. Here we present a computational model, lab-based, and online visual identification experiments to find corroborating evidence for this hypothesis in individuals without a formal ASD diagnosis. Our modeling predicts that artificially increasing noise results in SR for individuals with low internal noise (e.g., neurotypical), however not for those with higher internal noise (e.g., autistic, or neurotypical individuals with higher autistic traits). It also predicts that at low stimulus noise, individuals with higher internal noise outperform those with lower internal noise. We tested these predictions using visual identification tasks among participants from the general population with autistic traits measured by the Autism-Spectrum Quotient (AQ). While all participants showed SR in the lab-based experiment, this did not support our model strongly. In the online experiment, significant SR was not found, however participants with higher AQ scores outperformed those with lower AQ scores at low stimulus noise levels, which is consistent with our modeling. In conclusion, our study is the first to investigate the link between SR and superior performance by those with ASD-related traits, and reports limited evidence to support the high neural noise/SR hypothesis.

Electrical neuroimaging of voluntary audiospatial attention: evidence for a supramodal attention control network.

Previous attempts to investigate the supramodal nature of attentional control have focused primarily on identifying neuroanatomical overlap in the frontoparietal systems activated during voluntary shifts of spatial attention in different sensory modalities. However, the activation of the same neural structures is insufficient evidence for a supramodal system, as the same brain regions could interact with one another in very different ways during shifts of attention in different modalities. Thus, to explore the similarity of the functional networks, it is necessary to identify the neural structures involved and to examine the timing and sequence of activities within the network. To this end, we used an electrical neuroimaging technique to localize the neural sources of electroencephalographic signals recorded from human subjects during audiospatial shifts of attention and to examine the timing and sequence of activities within several regions of interest. We then compared the results to an analogous study of visuospatial attention shifts. Similar frontal and parietal regions were activated during visual and auditory shifts of attention, and the timing of activities within these regions was nearly identical. Following this modality-independent sequence of attention-control activity, activity in the relevant sensory cortex was enhanced in anticipation of the response-relevant target. These results are consistent with the hypothesis that a single supramodal network of frontal and parietal regions mediates voluntary shifts of spatial attention and controls the flow of sensory information in modality-specific sensory pathways.

Qualia and Phenomenal Consciousness Arise From the Information Structure of an Electromagnetic Field in the Brain.

In this paper we address the following problems and provide realistic answers to them: (1) What could be the physical substrate for subjective, phenomenal, consciousness (P-consciousness)? Our answer: the electromagnetic (EM) field generated by the movement and changes of electrical charges in the brain. (2) Is this substrate generated in some particular part of the brains of conscious entities or does it comprise the entirety of the brain/body? Our answer: a part of the thalamus in mammals, and homologous parts of other brains generates the critical EM field. (3) From whence arise the qualia experienced in P-consciousness? Our answer, the relevant EM field is "structured" by emulating in the brain the information in EM fields arising from both external (the environment) and internal (the body) sources. (4) What differentiates the P-conscious EM field from other EM fields, e.g., the flux of photons scattered from object surfaces, the EM field of an electro-magnet, or the EM fields generated in the brain that do not enter P-consciousness, such as those generated in the retina or occipital cortex, or those generated in brain areas that guide behavior through visual information in persons exhibiting "blindsight"? Our answer: living systems express a boundary between themselves and the environment, requiring them to model (coarsely emulate) information from their environment in order to control through actions, to the extent possible, the vast sea of variety in which they are immersed. This model, expressed in an EM field, is P-consciousness. The model is the best possible representation of the moment-to-moment niche-relevant (action-relevant: affordance) information an organism can generate (a Gestalt). Information that is at a lower level than niche-relevant, such as the unanalyzed retinal vector-field, is not represented in P-consciousness because it is not niche-relevant. Living organisms have sensory and other systems that have evolved to supply such information, albeit in a coarse form.

Phase offset determines alpha modulation of gamma phase coherence and hence signal transmission.

We find conditions for optimal phase coherence among sums of phase-offset sine wave pairs of two frequencies, e.g., gamma and alpha. Optimal phase coherence occurs when the respective phase offsets match. Then, using stochastic rate models instead of firing models for both cortical and pulvinar activity, we show that for roughly matching phase offsets of alpha and gamma oscillations there is optimal phase coherence and information transmission between modelled cortical regions.

Resting state network activation and functional connectivity in the dying brain.

OBJECTIVE: To characterize electrophysiological functional connectivity within both the default mode network (DMN) and the task-positive network (TPN) among a small group of unresponsive hospice patients at the end of life. METHODS: EEG recordings from resting state were analysed to identify brain regions in the DMN and TPN of 30 young, healthy controls, and of 9 hospice patients when they were responsive and of 5 patients when they became unresponsive during the last hours of life. RESULTS: The prevalence of activation and connectivity within the DMN was similar across all participant groups. Overall functional connectivity was higher between brain regions within the DMN than between brain regions within TPN for all participant groups. The number of functional connections within the DMN, however, was greater than those within the TPN among controls and responsive hospice patients but not among unresponsive hospice patients. CONCLUSIONS: Some unresponsive patients may have the functional architecture to support internally-oriented thought at the end of life. Resting state default mode - task positive network anticorrelations may be present among some unresponsive hospice patients. SIGNIFICANCE: Some unresponsive end of life patients may be able to mind-wander. Implications for internally-oriented awareness at the end of life are discussed.

Electrophysiological evidence of sustained attention to music among conscious participants and unresponsive hospice patients at the end of life.

OBJECTIVE: To characterize electrophysiological activity, and likely neural sources of that activity, associated with listening to music in both healthy participants and in a small group of hospice patients both when responsive and when unresponsive hours before death. METHODS: Young, healthy participants (N = 22) were asked to attend to (Active condition) and to ignore (Passive condition) brief (6 s) music excerpts. A smaller group (N = 13) of hospice patients was asked to attend to the same musical excerpts (Active condition only), both when they were responsive (N = 8) and again when they became unresponsive (N = 4) only hours before death. EEG-derived event-related spectral perturbations (ERSPs) to music stimuli, and their approximate neural sources, were computed for each individual in both groups. RESULTS: In the healthy participants, alpha-band ERSP during the music excerpts in a group-level analysis was significantly lower in posterio-parietal brain areas in the Active condition than in the Passive condition (event-related desynchronization, ERD). Moreover, in an analysis of individual ERSP data, most (18 of 22 or 84%) healthy participants showed meaningful sustained (4 or more seconds) alpha-band suppression in one or more posterio-parietal brain areas when they were asked to attend to the music, whereas far fewer healthy participants (only 7 of 19 or 37%) generated the same response when asked to ignore the music, indicating that posterio-parietal alpha-band ERD could be a useful marker of music listening. Similarly, 75% of eight responsive hospice patients, and 100% of four unresponsive hospice patients showed sustained posterio-parietal alpha-band suppression when asked to attend to the music, indicating that they could be listening to the music covertly even when overtly unresponsive. CONCLUSIONS: Some (but likely not all, as other patients will vary from those we studied) unresponsive patients at the end of life might be able to listen to music, despite being unable to overtly indicate their awareness. SIGNIFICANCE: Music stimulation may be a promising way to engage unresponsive patients.

The thalamic dynamic core theory of conscious experience.

I propose that primary conscious awareness arises from synchronized activity in dendrites of neurons in dorsal thalamic nuclei, mediated particularly by inhibitory interactions with thalamic reticular neurons. In support, I offer four evidential pillars: (1) consciousness is restricted to the results of cortical computations; (2) thalamus is the common locus of action of brain injury in vegetative state and of general anesthetics; (3) the anatomy and physiology of the thalamus imply a central role in consciousness; (4) neural synchronization is a neural correlate of consciousness.

Plastic systemic inhibition controls amplitude while allowing phase pattern in a stochastic neural field model.

We investigate oscillatory phase pattern formation and amplitude control for a linearized stochastic neuron field model by simulating Mexican-hat-coupled stochastic processes. We find, for several choices of parameters, that spatial pattern formation in the temporal phases of the coupled processes occurs if and only if their amplitudes are allowed to grow unrealistically large. Stimulated by recent work on homeostatic inhibitory plasticity, we introduce static and plastic (adaptive) systemic inhibitory mechanisms to keep the amplitudes stochastically bounded. We find that systems with static inhibition exhibited bounded amplitudes but no sustained phase patterns. With plastic systemic inhibition, on the other hand, the resulting systems exhibit both bounded amplitudes and sustained phase patterns. These results demonstrate that plastic inhibitory mechanisms in neural field models can dynamically control amplitudes while allowing patterns of phase synchronization to develop. Similar mechanisms of plastic systemic inhibition could play a role in regulating oscillatory functioning in the brain.

Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication.

It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development.

Electrophysiological evidence of preserved hearing at the end of life.

This study attempts to answer the question: "Is hearing the last to go?" We present evidence of hearing among unresponsive actively dying hospice patients. Individual ERP (MMN, P3a, and P3b) responses to deviations in auditory patterns are reported for conscious young, healthy control participants, as well as for hospice patients, both when the latter were conscious, and again when they became unresponsive to their environment. Whereas the MMN (and perhaps too the P3a) is considered an automatic response to auditory irregularities, the P3b is associated with conscious detection of oddball targets. All control participants, and most responsive hospice patients, evidenced a "local" effect (either a MMN, a P3a, or both) and some a "global" effect (P3b) to deviations in tone, or deviations in auditory pattern. Importantly, most unresponsive patients showed evidence of MMN responses to tone changes, and some showed a P3a or P3b response to either tone or pattern changes. Thus, their auditory systems were responding similarly to those of young, healthy controls just hours from end of life. Hearing may indeed be one of the last senses to lose function as humans die.

Large-scale gamma-band phase synchronization and selective attention.

Explaining the emergence of a coherent conscious percept and an intentional agent from the activity of distributed neurons is key to understanding how the brain produces higher cognitive processes. Gamma-band synchronization has been proposed to be a mechanism for the functional integration of neural populations that together form a transitory, large-scale, task- and/or percept-specific network. The operation of this mechanism in the context of attention orienting entails that cortical regions representing attended locations should show more gamma-band synchronization with other cortical areas than would those representing unattended locations. This increased synchronization should be apparent in the same time frame as that of the deployment of attention to a particular location. In order to observe this effect, we made electroencephalogram recordings while subjects attended to one side or the other of the visual field (which we confirmed by event-related potential analysis) and calculated phase-locking statistics between the signals recorded at relevant electrode pairs. We observed increased gamma-band phase synchronization between visual cortex contralateral to the attended location and other, widespread, cortical areas approximately 240-380 ms after the directional cue was presented, confirming the prediction of a large-scale gamma synchronous network oriented to the cued location.

Search asymmetry in a serial auditory task: Neural source analyses of EEG implicate attention strategies.

Here we report a detailed analysis of the fast network dynamics underlying P3a and P3b event-related potential (ERP) subcomponents generated during an unconventional serial auditory search paradigm. We dissect the electroencephalographic (EEG) data from an earlier study of ours, using a variety of advanced signal processing techniques, in order to discover how the brain is processing auditory targets differently when they possess a rare, salient, unpredictable feature not shared with distractors than when targets lack this feature but distractors have it. We find that brain regions associated with the Ventral Attention Network (VAN) are the primary neural generators of the P3a subcomponent in response to feature-present targets, whereas regions associated with the Dorsal Attention Network (DAN), as well as regions associated with detecting auditory oddball stimuli (ODD), may be the primary neural generators of the P3b, in the context of our study, and perhaps in search paradigms in general. Moreover, measurements of the time courses of oscillatory power changes and inter-regional synchronization in theta and low-gamma frequency bands were consistent with the early activation and synchronization within the VAN associated with the P3a subcomponent, and with the later activation and synchronization within the DAN and ODD networks associated with the P3b subcomponent. Implications of these finding for the mechanisms underlying search asymmetry phenomena are discussed.

Noise sharing and Mexican-hat coupling in a stochastic neural field.

A diffusion-type coupling operator that is biologically significant in neuroscience is a difference of Gaussian functions (Mexican-hat operator) used as a spatial-convolution kernel. We are interested in pattern formation by stochastic neural field equations, a class of space-time stochastic differential-integral equations using the Mexican-hat kernel. We explore quantitatively how the parameters that control the shape of the coupling kernel, the coupling strength, and aspects of spatially smoothed space-time noise influence the pattern in the resulting evolving random field. We confirm that a spatial pattern that is damped in time in a deterministic system may be sustained and amplified by stochasticity. We find that spatially smoothed noise alone causes pattern formation even without direct spatial coupling. Our analysis of the interaction between coupling and noise sharing allows us to determine parameter combinations that are optimal for the formation of spatial pattern.