Ketamine, propofol, and the EEG: A neural field analysis of HCN1-mediated interactions

Ketamine and propofol are two well-known, powerful anesthetic agents, yet at first sight this appears to be their only commonality. Ketamine is a dissociative anesthetic agent, whose main mechanism of action is considered to be N-methyl-D-aspartate (NMDA) antagonism; whereas propofol is a general anesthetic agent, which is assumed to primarily potentiate currents gated by γ-aminobutyric acid type A (GABAA) receptors. However, several experimental observations suggest a closer relationship. First, the effect of ketamine on the electroencephalogram (EEG) is markedly changed in the presence of propofol: on its own ketamine increases θ (4–8 Hz) and decreases α (8–13 Hz) oscillations, whereas ketamine induces a significant shift to beta band frequencies (13–30 Hz) in the presence of propofol. Second, both ketamine and propofol cause inhibition of the inward pacemaker current Ih, by binding to the corresponding hyperpolarization-activated cyclic nucleotide-gated potassium channel 1 (HCN1) subunit. The resulting effect is a hyperpolarization of the neuron’s resting membrane potential. Third, the ability of both ketamine and propofol to induce hypnosis is reduced in HCN1-knockout mice. Here we show that one can theoretically understand the observed spectral changes of the EEG based on HCN1-mediated hyperpolarizations alone, without involving the supposed main mechanisms of action of these drugs through NMDA and GABAA, respectively. On the basis of our successful EEG model we conclude that ketamine and propofol should be antagonistic to each other in their interaction at HCN1 subunits. Such a prediction is in accord with the results of clinical experiment in which it is found that ketamine and propofol interact in an infra-additive manner with respect to the endpoints of hypnosis and immobility.

Realistic mean field forward predictions for the integration of co-registered EEG/fMRI

Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

Dynamical complexity in a mean-field model of human EEG

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

Self-organized 40Hz synchronization in a physiological theory of EEG

We present evidence that large-scale spatial coherence of 40 Hz oscillations can emerge dynamically in a cortical mean field theory. The simulated synchronization time scale is about 150 ms, which compares well with experimental data on large-scale integration during cognitive tasks. The same model has previously provided consistent descriptions of the human EEG at rest, with tranquilizers, under anesthesia, and during anesthetic-induced epileptic seizures. The emergence of coherent gamma band activity is brought about by changing just one physiological parameter until cortex becomes marginally unstable for a small range of wavelengths. This suggests for future study a model of dynamic computation at the edge of cortical stability.

Understanding the effects of anesthetic agents on the EEG through neural field theory

Anesthetic and analgesic agents act through a diverse range of pharmacological mechanisms. Existing empirical data clearly shows that such "microscopic" pharmacological diversity is reflected in their "macroscopic" effects on the human electroencephalogram (EEG). Based on a detailed mesoscopic neural field model we theoretically posit that anesthetic induced EEG activity is due to selective parametric changes in synaptic efficacy and dynamics. Specifically, on the basis of physiologically constrained modeling, it is speculated that the selective modification of inhibitory or excitatory synaptic activity may differentially effect the EEG spectrum. Such results emphasize the importance of neural field theories of brain electrical activity for elucidating the principles whereby pharmacological agents effect the EEG. Such insights will contribute to improved methods for monitoring depth of anesthesia using the EEG.

Immediate auditory repetition of words and nonwords: An ERP study of lexical and sublexical processing

ERPs were elicited to (1) words, (2) pseudowords derived from these words, and (3) nonwords with no lexical neighbors, in a task involving listening to immediately repeated auditory stimuli. There was a significant early (P200) effect of phonotactic probability in the first auditory presentation, which discriminated words and pseudowords from nonwords; and a significant somewhat later (N400) effect of lexicality, which discriminated words from pseudowords and nonwords. There was no reliable effect of lexicality in the ERPs to the second auditory presentation. We conclude that early sublexical phonological processing differed according to phonotactic probability of the stimuli, and that lexically-based redintegration occurred for words but did not occur for pseudowords or nonwords. Thus, in online word recognition and immediate retrieval, phonological and/or sublexical processing plays a more important role than lexical level redintegration.

Auditory distraction in memory tasks: Can it be controlled?

Irrelevant sound accompanying the processes of encoding and retrieval of verbal events impairs memory performance. However, the degree of impairment is highly dependent on a range of factors. Some of them lie outside rememberers’ control, like the semantic content of distracting sound or the nature of a test used to assess memory. Others, like a strategy used to encode memoranda, rest under control of the rememberer. In this paper the factors that modulate memory impairment are outlined and discussed in terms of multiple mechanisms contributing to memory impairment under auditory distraction. The mechanisms of a capture of attention by distraction, interference of automatic seriation of distraction and voluntary seriation of memoranda, semantic inhibition of distraction, and blocking of memoranda by semantically related distracters are described. Results that demonstrate how these mechanisms determine memory impairment under auditory distraction are also discussed. Particular attention is devoted to the possibility of voluntary control over the workings of these mechanisms and the conditions under which the negative impact of auditory distraction upon memory performance could be minimised.

Metacognitive control over memory processes under auditory distraction

Decades of research attest that memory processes suffer under conditions of auditory distraction. What is however less well understood is whether people are able to modify how their memory processes are deployed in order to compensate for disruptive effects of distraction. The metacognitive approach to memory describes a variety of ways people can exert control over their cognitive processes to optimize performance. Here we describe our recent investigations into how these control processes change under conditions of auditory distraction. We specifically looked at control of encoding in the form of decisions about how long to study a word when it is presented and control of memory reporting in the form of decisions whether to volunteer or withhold retrieved details. Regarding control of encoding, we expected that people would compensate for disruptive effects of distraction by extending study time under noise. Our results revealed, however, that when exposed to irrelevant speech, people curtail rather than extend study. Regarding control of memory reporting, we expected that people would compensate for the loss of access to memory records by volunteering responses held with lower confidence. Our results revealed, however, that people’s reporting strategies do not differ when memory task is performed in silence or under auditory distraction, although distraction seriously undermines people’s confidence in their own responses. Together, our studies reveal novel avenues for investigating the psychological effects of auditory distraction within a metacognitive framework.

Proposal of a floating mechanism based on magnetic levitation method toward EEG-driven robotic system

We discussed a floating mechanism based on quasi-magnetic levitation method that can be attached at the endpoint of a robot arm in order to construct a novel redundant robot arm for producing compliant motions. The floating mechanism can be composed of magnets and a constraint mechanism such that the repelling force of the magnets floats the endpoint part of the mechanism stable for the guided motions. The analytical and experimental results show that the proposed floating mechanism can produce stable floating motions with small inertia and viscosity. The results also show that the proposed mechanism can detect small force applied to the endpoint part because the friction force of the mechanism is very small.

Novel single trial movement classification based on temporal dynamics of EEG

Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis was performed on the EEG signals to find robust markers of movement detection. The evolution of the autocorrelation function was characterised via the relaxation time of the autocorrelation by exponential curve fitting. It was observed that the decay constant of the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%.

Mismatch Negativity (MMN) reveals inefficient auditory ventral stream function in chronic auditory comprehension impairments

Background: Auditory discrimination is significantly impaired in Wernicke’s aphasia (WA) and thought to be causatively related to the language comprehension impairment which characterises the condition. This study used mismatch negativity (MMN) to investigate the neural responses corresponding to successful and impaired auditory discrimination in WA. Methods: Behavioural auditory discrimination thresholds of CVC syllables and pure tones were measured in WA (n=7) and control (n=7) participants. Threshold results were used to develop multiple-deviant mismatch negativity (MMN) oddball paradigms containing deviants which were either perceptibly or non-perceptibly different from the standard stimuli. MMN analysis investigated differences associated with group, condition and perceptibility as well as the relationship between MMN responses and comprehension (within which behavioural auditory discrimination profiles were examined). Results: MMN waveforms were observable to both perceptible and non-perceptible auditory changes. Perceptibility was only distinguished by MMN amplitude in the PT condition. The WA group could be distinguished from controls by an increase in MMN response latency to CVC stimuli change. Correlation analyses displayed relationship between behavioural CVC discrimination and MMN amplitude in the control group, where greater amplitude corresponded to better discrimination. The WA group displayed the inverse effect; both discrimination accuracy and auditory comprehension scores were reduced with increased MMN amplitude. In the WA group, a further correlation was observed between the lateralisation of MMN response and CVC discrimination accuracy; the greater the bilateral involvement the better the discrimination accuracy. Conclusions: The results from this study provide further evidence for the nature of auditory comprehension impairment in WA and indicate that the auditory discrimination deficit is grounded in a reduced ability to engage in efficient hierarchical processing and the construction of invariant auditory objects. Correlation results suggest that people with chronic WA may rely on an inefficient, noisy right hemisphere auditory stream when attempting to process speech stimuli.

Contrasting effects of changing rhythm and content on auditory distraction in immediate memory

Across five experiments, the temporal regularity and content of an irrelevant speech stream were varied and their effects on a serial recall task examined. Variations of the content, but not the rhythm, of the irrelevant speech stimuli reliably disrupted serial recall performance in all experiments. Bayesian analyses supported the null hypothesis over the hypothesis that irregular rhythms would disrupt memory to a greater extent than regular rhythms. Pooling the data in a combined analysis revealed that regular presentation of the irrelevant speech was significantly more disruptive to serial recall than irregular presentation. These results are consistent with the idea that auditory distraction is sensitive to both intra-item and inter-item relations and challenge an orienting-based account of auditory distraction.

Neural correlates of emotional responses to music: an EEG study

This paper presents an EEG study into the neural correlates of music-induced emotions. We presented participants with a large dataset containing musical pieces in different styles, and asked them to report on their induced emotional responses. We found neural correlates of music-induced emotion in a number of frequencies over the pre-frontal cortex. Additionally, we found a set of patterns of functional connectivity, defined by inter-channel coherence measures,to be significantly different between groups of music-induced emotional responses.

Memo test: standardisation of computerised assessment of auditory verbal short-term memory

Short-term memory (STM) impairments are prevalent in adults with acquired brain injuries. While there are several published tests to assess these impairments, the majority require speech production, e.g. digit span (Wechsler, 1987). This feature may make them unsuitable for people with aphasia and motor speech disorders because of word finding difficulties and speech demands respectively. If patients perceive the speech demands of the test to be high, the may not engage with testing. Furthermore, existing STM tests are mainly ‘pen-and-paper’ tests, which can jeopardise accuracy. To address these shortcomings, we designed and standardised a novel computerised test that does not require speech output and because of the computerised delivery it would enable clinicians identify STM impairments with greater precision than current tests. The matching listening span tasks, similar to the non-normed PALPA 13 (Kay, Lesser & Coltheart, 1992) is used to test short-term memory for serial order of spoken items. Sequences of digits are presented in pairs. The person hears the first sequence, followed by the second sequence and s/he decides whether the two sequences are the same or different. In the computerised test, the sequences are presented in live voice recordings on a portable computer through a software application (Molero Martin, Laird, Hwang & Salis 2013). We collected normative data from healthy older adults (N=22-24) using digits, real words (one- and two-syllables) and non-words (one- and two- syllables). Their performance was scored following two systems. The Highest Span system was the highest span length (e.g. 2-8) at which a participant correctly responded to over 7 out of 10 trials at the highest sequence length. Test re-test reliability was also tested in a subgroup of participants. The test will be available as free of charge for clinicians and researchers to use.

Motor imagery-induced EEG patterns in individuals with spinal cord injury and their impact on brain–computer interface accuracy

Objective. Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no ‘cure’ at the present time. Brain–computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. Approach. Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. Main results. It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). Significance. The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals