Dynamics of coupled thalamocortical modules

Revolutionizing treatment for disorders of consciousness: a multidisciplinary review of advancements in deep brain stimulation

Among the existing research on the treatment of disorders of consciousness (DOC), deep brain stimulation (DBS) offers a highly promising therapeutic approach. This comprehensive review documents the historical development of DBS and its role in the treatment of DOC, tracing its progression from an experimental therapy to a detailed modulation approach based on the mesocircuit model hypothesis. The mesocircuit model hypothesis suggests that DOC arises from disruptions in a critical network of brain regions, providing a framework for refining DBS targets. We also discuss the multimodal approaches for assessing patients with DOC, encompassing clinical behavioral scales, electrophysiological assessment, and neuroimaging techniques methods. During the evolution of DOC therapy, the segmentation of central nuclei, the recording of single-neurons, and the analysis of local field potentials have emerged as favorable technical factors that enhance the efficacy of DBS treatment. Advances in computational models have also facilitated a deeper exploration of the neural dynamics associated with DOC, linking neuron-level dynamics with macroscopic behavioral changes. Despite showing promising outcomes, challenges remain in patient selection, precise target localization, and the determination of optimal stimulation parameters. Future research should focus on conducting large-scale controlled studies to delve into the pathophysiological mechanisms of DOC. It is imperative to further elucidate the precise modulatory effects of DBS on thalamo-cortical and cortico-cortical functional connectivity networks. Ultimately, by optimizing neuromodulation strategies, we aim to substantially enhance therapeutic outcomes and greatly expedite the process of consciousness recovery in patients.

Therapies to Restore Consciousness in Patients with Severe Brain Injuries: A Gap Analysis and Future Directions

Background/Objective

For patients with disorders of consciousness (DoC) and their families, the search for new therapies has been a source of hope and frustration. Almost all clinical trials in patients with DoC have been limited by small sample sizes, lack of placebo groups, and use of heterogeneous outcome measures. As a result, few therapies have strong evidence to support their use; amantadine is the only therapy recommended by current clinical guidelines, specifically for patients with DoC caused by severe traumatic brain injury. To foster and advance development of consciousness-promoting therapies for patients with DoC, the Curing Coma Campaign convened a Coma Science Work Group to perform a gap analysis.

Methods

We consider five classes of therapies: (1) pharmacologic; (2) electromagnetic; (3) mechanical; (4) sensory; and (5) regenerative. For each class of therapy, we summarize the state of the science, identify gaps in knowledge, and suggest future directions for therapy development.

Results

Knowledge gaps in all five therapeutic classes can be attributed to the lack of: (1) a unifying conceptual framework for evaluating therapeutic mechanisms of action; (2) large-scale randomized controlled trials; and (3) pharmacodynamic biomarkers that measure subclinical therapeutic effects in early-phase trials. To address these gaps, we propose a precision medicine approach in which clinical trials selectively enroll patients based upon their physiological receptivity to targeted therapies, and therapeutic effects are measured by complementary behavioral, neuroimaging, and electrophysiologic endpoints.

Conclusions

This personalized approach can be realized through rigorous clinical trial design and international collaboration, both of which will be essential for advancing the development of new therapies and ultimately improving the lives of patients with DoC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12028-021-01227-y.

Median nerve stimulation induced motor learning in healthy adults: A study of timing of stimulation and type of learning

Median nerve stimulation (MNS) has been shown to change brain metaplasticity over the somatosensory networks, based on a bottom-up mechanism and may improve motor learning. This exploratory study aimed to test the effects of MNS on implicit and explicit motor learning as measured by the serial reaction time task (SRTT) using a double-blind, sham-controlled, randomized trial, in which participants were allocated to one of three groups: (a) online active MNS during acquisition, (b) offline active MNS during early consolidation and (c) sham MNS. SRTT was performed at baseline, during the training phase (acquisition period), and 30 min after training. We assessed the effects of MNS on explicit and implicit motor learning at the end of the training/acquisition period and at retest. The group receiving online MNS (during acquisition) showed a significantly higher learning index for the explicit sequences compared to the offline group (MNS during early consolidation) and the sham group. The offline group also showed a higher learning index as compared to sham. Additionally, participants receiving online MNS recalled the explicit sentence significantly more than the offline MNS and sham groups. MNS effects on motor learning have a specific effect on type of learning (explicit vs. implicit) and are dependent on timing of stimulation (during acquisition vs. early consolidation). More research is needed to understand and optimize the effects of peripheral electrical stimulation on motor learning. Taken together, our results show that MNS, especially when applied during the acquisition phase, is a promising tool to modulate motor leaning.

Stimulus-induced transitions between spike-wave discharges and spindles with the modulation of thalamic reticular nucleus

It is believed that thalamic reticular nucleus (TRN) controls spindles and spike-wave discharges (SWD) in seizure or sleeping processes. The dynamical mechanisms of spatiotemporal evolutions between these two types of activity, however, are not well understood. In light of this, we first use a single-compartment thalamocortical neural field model to investigate the effects of TRN on occurrence of SWD and its transition. Results show that the increasing inhibition from TRN to specific relay nuclei (SRN) can lead to the transition of system from SWD to slow-wave oscillation. Specially, it is shown that stimulations applied in the cortical neuronal populations can also initiate the SWD and slow-wave oscillation from the resting states under the typical inhibitory intensity from TRN to SRN. Then, we expand into a 3-compartment coupled thalamocortical model network in linear and circular structures, respectively, to explore the spatiotemporal evolutions of wave states in different compartments. The main results are: (i) for the open-ended model network, SWD induced by stimulus in the first compartment can be transformed into sleep-like slow UP-DOWN and spindle states as it propagates into the downstream compartments; (ii) for the close-ended model network, weak stimulations performed in the first compartment can result in the consistent experimentally observed spindle oscillations in all three compartments; in contrast, stronger periodic single-pulse stimulations applied in the first compartment can induce periodic transitions between SWD and spindle oscillations. Detailed investigations reveal that multi-attractor coexistence mechanism composed of SWD, spindles and background state underlies these state evolutions. What's more, in order to demonstrate the state evolution stability with respect to the topological structures of neural network, we further expand the 3-compartment coupled network into 10-compartment coupled one, with linear and circular structures, and nearest-neighbor (NN) coupled network as well as its realization of small-world (SW) topology via random rewiring, respectively. Interestingly, for the cases of linear and circular connetivities, qualitatively similar results were obtained in addition to the more irregularity of firings. However, SWD can be eventually transformed into the consistent low-amplitude oscillations for both NN and SW networks. In particular, SWD evolves into the slow spindling oscillations and background tonic oscillations within the NN and SW network, respectively. Our modeling and simulation studies highlight the effect of network topology in the evolutions of SWD and spindling oscillations, which provides new insights into the mechanisms of cortical seizures development.

The pacemaker role of thalamic reticular nucleus in controlling spike-wave discharges and spindles

Absence epilepsy, characterized by 2-4 Hz spike-wave discharges (SWDs), can be caused by pathological interactions within the thalamocortical system. Cortical spindling oscillations are also demonstrated to involve the oscillatory thalamocortical rhythms generated by the synaptic circuitry of the thalamus and cortex. This implies that SWDs and spindling oscillations can share the common thalamocortical mechanism. Additionally, the thalamic reticular nucleus (RE) is hypothesized to regulate the onsets and propagations of both the epileptic SWDs and sleep spindles. Based on the proposed single-compartment thalamocortical neural field model, we firstly investigate the stimulation effect of RE on the initiations, terminations, and transitions of SWDs. It is shown that the activations and deactivations of RE triggered by single-pulse stimuli can drive the cortical subsystem to behave as the experimentally observed onsets and self-abatements of SWDs, as well as the transitions from 2-spike and wave discharges (2-SWDs) to SWDs. In particular, with increasing inhibition from RE to the specific relay nucleus (TC), rich transition behaviors in cortex can be obtained through the upstream projection path, RE→TC→Cortex. Although some of the complex dynamical patterns can be expected from the earlier single compartment thalamocortical model, the effect of brain network topology on the emergence of SWDs and spindles, as well as the transitions between them, has not been fully investigated. We thereby develop a spatially extended 3-compartment coupled network model with open-/closed-end connective configurations, to investigate the spatiotemporal effect of RE on the SWDs and spindles. Results show that the degrees of activations of RE₁ can induce the rich spatiotemporal evolution properties including the propagations from SWDs to spindles within different compartments and the transitions between them, through the RE₁→TC₁→Cortex₁ and Cortex₁→Cortex₂→Cortex₃ projecting paths, respectively. Overall, those results imply that RE possesses the pacemaker function in controlling SWDs and spindling oscillations, which computationally provide causal support for the involvement of RE in absence seizures and sleep spindles.

Developing a neuropsychological measurement to capture workplace learning

Purpose

The purpose of the paper is to examine variables to be included in a measurement instrument which measures workplace learning related to recent research into quality management and brain functioning.

Design/methodology/approach

A literature review was conducted, investigating measures of workplace learning as well as the connections between brain functioning and management. Further studies will use the brain integration scale to compare levels of brain integration with measures of workplace learning.

Findings

The variables “empathy”, “presence and communication”, “continuity”, “influence”, “development”, “work-integrated learning” and “flow” were found to be relevant from the literature review to be tested for inclusion in the measurement instrument. A measurement model with these variables included has been developed.

Research limitations/implications

This paper is conceptual in its nature. Empirical studies are needed to validate the propositions.

Practical implications

The proposed measurement instrument can be used by managers to gain insight into underlying mechanisms in the organizational culture that influence employees’ learning and potential for development. Thus, it can aid managers to achieve profound learning in their organizations, which is necessary for continuously maintaining high quality of products and services.

Social implications

For society, the implementation of the proposed measurement instrument in companies could lead to better health and higher job satisfaction among employees.

Originality/value

Traditional ways of measuring working environment are rarely connected to brain functioning of the employees. Only requiring small resources, this approach adds to an understanding of underlying mechanisms.

Behavioral effects of transcranial pulsed current stimulation (tPCS): Speed-accuracy tradeoff in attention switching task

Transcranial pulsed current stimulation (tPCS) has been shown to increase inter-hemispheric coherence of brain oscillatory activity, mainly in fronto-temporal regions, leading to enhancement of functional connectivity across neural networks. The question is whether tPCS can modulate behavior significantly. Our aim was to identify the effects of tPCS on paired associative learning task (PALT) and attention switching task (AST), and to further categorize physiological autonomic responses by heart rate variability and electrodermal activity measurements before and after task performance. Thirty healthy volunteers were randomized to receive a single session of sham or active 2mA tPCS stimulation with a random frequency between 1 and 5Hz. We show that active tPCS significantly improved response time in the AST compared to sham stimulation, so that subjects who received active tPCS significantly exhibit decreased switching cost between repeat and switch trials. No differences were found in response accuracy on AST and PALT. No significant changes were observed in physiological parameters. Based on our results, we suggest that tPCS has a more pronounced effect on tasks that require the increase of functional connectivity across pre-existent neural circuitry, rather than on tasks that require the development of new learning circuits or the creation of new connections.

How the cortico-thalamic feedback affects the EEG power spectrum over frontal and occipital regions during propofol-induced sedation

Increasing concentrations of the anaesthetic agent propofol initially induces sedation before achieving full general anaesthesia. During this state of anaesthesia, the observed specific changes in electroencephalographic (EEG) rhythms comprise increased activity in the δ- (0.5-4 Hz) and α- (8-13 Hz) frequency bands over the frontal region, but increased δ- and decreased α-activity over the occipital region. It is known that the cortex, the thalamus, and the thalamo-cortical feedback loop contribute to some degree to the propofol-induced changes in the EEG power spectrum. However the precise role of each structure to the dynamics of the EEG is unknown. In this paper we apply a thalamo-cortical neuronal population model to reproduce the power spectrum changes in EEG during propofol-induced anaesthesia sedation. The model reproduces the power spectrum features observed experimentally both in frontal and occipital electrodes. Moreover, a detailed analysis of the model indicates the importance of multiple resting states in brain activity. The work suggests that the α-activity originates from the cortico-thalamic relay interaction, whereas the emergence of δ-activity results from the full cortico-reticular-relay-cortical feedback loop with a prominent enforced thalamic reticular-relay interaction. This model suggests an important role for synaptic GABAergic receptors at relay neurons and, more generally, for the thalamus in the generation of both the δ- and the α- EEG patterns that are seen during propofol anaesthesia sedation.

Large-scale brain dynamics in disorders of consciousness

Brain injury profoundly affects global brain dynamics, and these changes are manifest in the electroencephalogram (EEG). Despite the heterogeneity of injury mechanisms and the modularity of brain function, there is a commonality of dynamical features that characterize the EEG along the gamut from coma to recovery. After severest injury, EEG activity is concentrated below 1 Hz. In minimally conscious state during wakefulness, there is a peak of activity in the 3-7 Hz range, often coherent across the brain, and often also activity in the beta (15-30 Hz) range. These spectral changes likely result from varying degrees of functional deafferentation at thalamic and cortical levels. EEG-based indices of brain dynamics that go beyond these simple spectral measures may provide further diagnostic information and physiologic insights.

Thalamo-cortical mechanisms underlying changes in amplitude and frequency of human alpha oscillations

Although a large number of studies have been devoted to establishing correlations between changes in amplitude and frequency of EEG alpha oscillations and cognitive processes, it is currently unclear through which physiological mechanisms such changes are brought about. In this study we use a biophysical model of EEG generation to gain a fundamental understanding of the functional changes within the thalamo-cortical system that might underly such alpha responses. The main result of this study is that, although the physiology of the thalamo-cortical system is characterized by a large number of parameters, alpha responses effectively depend on only three variables. Physiologically, these variables determine the resonance properties of feedforward, cortico-thalamo-cortical, and intra-cortical circuits. By examining the effect of modulations of these resonances on the amplitude and frequency of EEG alpha oscillations, it is established that the model can reproduce the variety of experimentally observed alpha responses, as well as the experimental finding that changes in alpha amplitude are typically an order of magnitude larger than changes in alpha frequency. The modeling results are also in line with the fact that alpha responses often correlate linearly with indices characterizing cognitive processes. By investigating the effect of synaptic and intrinsic neuronal parameters, we find that alpha responses reflect changes in cortical activation, which is consistent with the hypothesis that alpha activity serves to selectively inhibit cortical regions during cognitive processing demands. As an example of how these analyses can be applied to specific experimental protocols, we reproduce benzodiazepine-induced alpha responses and clarify the putative underlying thalamo-cortical mechanisms. The findings reported in this study provide a fundamental physiological framework within which alpha responses observed in specific experimental protocols can be understood.

Cognitive and perceptual functions of the visual thalamus

The thalamus is classically viewed as passively relaying information to the cortex. However, there is growing evidence that the thalamus actively regulates information transmission to the cortex and between cortical areas using a variety of mechanisms, including the modulation of response magnitude, firing mode, and synchrony of neurons according to behavioral demands. We discuss how the visual thalamus contributes to attention, awareness, and visually guided actions, to present a general role for the thalamus in perception and cognition.

Mean-field modeling of thalamocortical dynamics and a model-driven approach to EEG analysis

Higher brain function depends on task-dependent information flow between cortical regions. Converging lines of evidence suggest that interactions between cortical regions and the central thalamus play a key role in establishing the dynamic patterns of functional connectivity that normally support these processes. In patients with chronic disturbances of cognitive function due to severe brain injury, dysfunction of this circuitry likely plays a crucial role in pathogenesis. However, assaying thalamocortical interactions is challenging even in healthy subjects and more so in severely impaired patients. To approach this problem, we apply a dynamical-systems approach to motivate an analysis of the electroencephalogram (EEG). We begin with a model for a single thalamocortical module [Robinson PA, Rennie CJ, Rowe DL (2002) Phys Rev E Stat Nonlin Soft Matter Phys 65:041924; Robinson PA, Rennie CJ, Wright JJ, Bourke PD (1998) Phys Rev E Stat Nonlin Soft Matter Phys 58:3557-3571]. When two such modules interact via shared thalamic inhibition, multistable behavior emerges; each mode is characterized by a different pattern of coherence between cortical regions. This observation suggests that changing patterns of cortical coherence are a hallmark of normal thalamocortical dynamics. In a preliminary study, we test this idea by analyzing the EEG of a patient with chronic brain injury, who has a marked improvement in behavior and frontal brain metabolism in response to zolpidem. The analysis shows that following zolpidem administration, changing patterns of coherence are identified between the frontal lobes and between frontal and distant brain regions. These observations support the role of the central thalamus in the organization of patterns of cortical interactions and suggest how indexes of thalamocortical dynamics can be extracted from the EEG.

Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals

Modular architecture is a hallmark of many brain circuits. In the cerebral cortex, in particular, it has been observed that reciprocal connections are often present between functionally interconnected areas that are hierarchically organized. We investigate the effect of reciprocal connections in a network of modules of simulated spiking neurons. The neural activity is recorded by means of virtual electrodes and EEG-like signals, called electrochipograms (EChG), analyzed by time- and frequency-domain methods. A major feature of our approach is the implementation of important bio-inspired processes that affect the connectivity within a neural module: synaptogenesis, cell death, spike-timing-dependent plasticity and synaptic pruning. These bio-inspired processes drive the build-up of auto-associative links within each module, which generate an areal activity, recorded by EChG, that reflect the changes in the corresponding functional connectivity within and between neuronal modules. We found that circuits with intra-layer reciprocal projections exhibited enhanced stimulus-locked response. We show evidence that all networks of modules are able to process and maintain patterns of activity associated with the stimulus after its offset. The presence of feedback and horizontal projections was necessary to evoke cross-layer coherence in bursts of -frequency at regular intervals. These findings bring new insights to the understanding of the relation between the functional organization of neural circuits and the electrophysiological signals generated by large cell assemblies. This article is part of a Special Issue entitled "Neural Coding".