Corticothalamic System Research Articles

Integration of distinct cortical inputs to primary and higher order inhibitory cells of the thalamus.

The necortex regulates its own sensory input in part through top-down inhibitory mechanisms. Descending corticothalamic projections drive GABAergic neurons of the thalamic reticular nucleus (TRN), which then control thalamocortical cells via inhibition. Neurons in sensory TRN are organized into primary and higher order (HO) subpopulations, with separate intrathalamic connections and distinct genetic and functional properties. Here, we investigated top-down neocortical control over primary and HO neurons of somatosensory TRN. Projections from layer 6 of somatosensory cortex evoked stronger and more state-dependent activity in primary than in HO TRN, driven by more robust synaptic inputs and potent T-type calcium currents. However, HO TRN received additional, physiologically distinct, inputs from layer 5 of S1 and motor cortex. Thus, in a departure from the canonical focused sensory layer 6 innervation characteristic of primary TRN, HO TRN integrates broadly from multiple corticothalamic systems, with unique state-dependence, extending the range of mechanisms for top-down control.

Neural field theory of adaptive effects on auditory evoked responses and mismatch negativity in multifrequency stimulus sequences.

Physiologically based neural field theory (NFT) of the corticothalamic system, including adaptation, is used to calculate the responses evoked by trains of auditory stimuli that differ in frequency. In oddball paradigms, fully distinguishable frequencies lead to different standard (common stimulus) and deviant (rare stimulus) responses; the signal obtained by subtracting the standard response from the deviant is termed the mismatch negativity (MMN). In this analysis, deviant responses are found to correspond to unadapted cortex, whereas the part of auditory cortex that processes the standard stimuli adapts over several stimulus presentations until the final standard response form is achieved. No higher-order memory processes are invoked. In multifrequency experiments, the deviant response approaches the standard one as the deviant frequency approaches that of the standard and analytic criteria for this effect to be obtained. It is shown that these criteria can also be used to understand adaptation in random tone sequences. A method of probing MMNs and adaptation in random tone sequences is suggested to makes more use of such data.

Injury to thalamocortical projections following traumatic brain injury results in attractor dynamics for cortical networks.

Major theories of consciousness predict that complex electroencephalographic (EEG) activity is required for consciousness, yet it is not clear how such activity arises in the corticothalamic system. The thalamus is well-known to control cortical excitability via interlaminar projections, but whether thalamic input is needed for complexity is not known. We hypothesized that the thalamus facilitates complex activity by adjusting synaptic connectivity, thereby increasing the availability of different configurations of cortical neurons (cortical "states"), as well as the probability of state transitions. To test this hypothesis, we characterized EEG activity from prefrontal cortex (PFC) in traumatic brain injury (TBI) patients with and without injuries to thalamocortical projections, measured with diffusion tensor imaging (DTI). We found that injury to thalamic projections (especially from the mediodorsal thalamus) was strongly associated with unconsciousness and delta-band EEG activity. Using advanced signal processing techniques, we found that lack of thalamic input led to 1.) attractor dynamics for cortical networks with a tendency to visit the same states, 2.) a reduced repertoire of possible states, and 3.) high predictability of transitions between states. These results imply that complex PFC activity associated with consciousness depends on thalamic input. Our model implies that restoration of cortical connectivity is a critical function of the thalamus after brain injury. We draw a critical connection between thalamic input and complex cortical activity associated with consciousness.

Seizure Prediction in Genetic Rat Models of Absence Epilepsy: Improved Performance through Multiple-Site Cortico-Thalamic Recordings Combined with Machine Learning.

Seizure prediction is the grand challenge of epileptology. However, effort was devoted to prediction of focal seizures, while generalized seizures were regarded as stochastic events. Long-lasting local field potential (LFP) recordings containing several hundred generalized spike and wave discharges (SWDs), acquired at eight locations in the cortico-thalamic system of absence epileptic rats, were iteratively analyzed in all possible combinations of either two or three recording sites, by a wavelet-based algorithm, calculating the product of the wavelet-energy signaling increases in synchronicity. Sensitivity and false alarm rate of prediction were compared between various combinations, and wavelet spectra of true and false positive predictions were fed to a random forest machine learning algorithm to further differentiate between them. Wavelet analysis of intracortical and cortico-thalamic LFP traces showed a significantly smaller number of false alarms compared with intrathalamic combinations, while predictions based on recordings in Layers IV, V, and VI of the somatosensory-cortex significantly outreached all other combinations in terms of prediction sensitivity. In 24-h out-of-sample recordings of nine Genetic Absence Epilepsy Rats from Strasbourg (GAERS), containing diurnal fluctuations of SWD occurrence, classification of true and false positives by the trained random forest further reduced the false alarm rate by 71%, although at some trade-off between false alarms and sensitivity of prediction, as reflected in relatively low F1 score values. Results provide support for the cortical-focus theory of absence epilepsy and allow the conclusion that SWDs are predictable to some degree. The latter paves the way for the development of closed-loop SWD prediction-prevention systems. Suggestions for a possible translation to human data are outlined.

Complement factor C1q mediates sleep spindle loss and epileptic spikes after mild brain injury.

Although traumatic brain injury (TBI) acutely disrupts the cortex, most TBI-related disabilities reflect secondary injuries that accrue over time. The thalamus is a likely site of secondary damage because of its reciprocal connections with the cortex. Using a mouse model of mild TBI (mTBI), we found a chronic increase in C1q expression specifically in the corticothalamic system. Increased C1q expression colocalized with neuron loss and chronic inflammation and correlated with disruption in sleep spindles and emergence of epileptic activities. Blocking C1q counteracted these outcomes, suggesting that C1q is a disease modifier in mTBI. Single-nucleus RNA sequencing demonstrated that microglia are a source of thalamic C1q. The corticothalamic circuit could thus be a new target for treating TBI-related disabilities.

Neural Field Theory of Evoked Response Sequences and Mismatch Negativity With Adaptation.

Physiologically based neural field theory of the corticothalamic system is used to calculate the responses evoked by trains of auditory stimuli that correspond to different cortical locations via the tonotopic map. The results are shown to account for standard and deviant evoked responses to frequent and rare stimuli, respectively, in the auditory oddball paradigms widely used in human cognitive studies, and the so-called mismatch negativity between them. It also reproduces a wide range of other effects and variants, including the mechanism by which a change in standard responses relative to deviants can develop through adaptation, different responses when two deviants are presented in a row or a standard is presented after two deviants, relaxation of standard responses back to deviant form after a stimulus-free period, and more complex sequences. Some cases are identified in which adaptation does not account for the whole difference between standard and deviant responses. The results thus provide a systematic means to determine how much of the response is due to adaptation in the system comprising the primary auditory cortex and medial geniculate nucleus, and how much requires involvement of higher-level processing.

Evoked response activity eigenmode analysis in a convoluted cortex via neural field theory.

Neural field theory of the corticothalamic system is used to explore evoked response potentials (ERPs) caused by spatially localized impulse stimuli on the convoluted cortex and on a spherical cortex. Eigenfunctions are calculated analytically on the spherical cortex and numerically on the convoluted cortex via eigenfunction expansions. Eigenmodes on a convoluted cortex are similar to those of the spherical cortex, and a few such modes are found to be sufficient to reproduce the main ERP features. It is found that the ERP peak is stronger in spherical cortex than convoluted cortex, but in both cases the peak decreases monotonically with increasing distance from the stimulus point. In the convoluted case, cortical folding causes ERPs to differ between locations at the same distance from the stimulus point and spherical symmetries are only approximately preserved.

Chemogenetics Reveal an Anterior Cingulate-Thalamic Pathway for Attending to Task-Relevant Information.

In a changing environment, organisms need to decide when to select items that resemble previously rewarded stimuli and when it is best to switch to other stimulus types. Here, we used chemogenetic techniques to provide causal evidence that activity in the rodent anterior cingulate cortex and its efferents to the anterior thalamic nuclei modulate the ability to attend to reliable predictors of important outcomes. Rats completed an attentional set-shifting paradigm that first measures the ability to master serial discriminations involving a constant stimulus dimension that reliably predicts reinforcement (intradimensional-shift), followed by the ability to shift attention to a previously irrelevant class of stimuli when reinforcement contingencies change (extradimensional-shift). Chemogenetic disruption of the anterior cingulate cortex (Experiment 1) as well as selective disruption of anterior cingulate efferents to the anterior thalamic nuclei (Experiment 2) impaired intradimensional learning but facilitated 2 sets of extradimensional-shifts. This pattern of results signals the loss of a corticothalamic system for cognitive control that preferentially processes stimuli resembling those previously associated with reward. Previous studies highlight a separate medial prefrontal system that promotes the converse pattern, that is, switching to hitherto inconsistent predictors of reward when contingencies change. Competition between these 2 systems regulates cognitive flexibility and choice.

Electromagnetic radiation from memristor applied to basal ganglia helps in controlling absence seizures

We study a model modified from basal ganglia corticothalamic network to explore the occurrence of absence seizures under the effect of electromagnetic radiation from a memristor. Absence seizure activities have been studied by varying the coupling strength of TRN-SRN pathway and the synaptic kinetics of $$\hbox {GABA}_{B}$$ receptors on TRN. It has been seen from the numerical simulations that when electromagnetic radiation from a memristor is applied to basal ganglia, spike and wave discharge oscillation region characteristic of absence seizure phenomenon has been reduced considerably. The combined action of electromagnetic radiation and inhibitory SNr-TRN and SNr-SRN pathways has also been investigated. The results show that presence of electromagnetic radiation aids in suppressing the formation of absence seizure activities in corticothalamic system. Our computational results may help to provide an insight in the treatment of real absence epilepsy patients.

Sleep and Epilepsy Link by Plasticity.

We aimed to explore the link between NREM sleep and epilepsy. Based on human and experimental data we propose that a sleep-related epileptic transformation of normal neurological networks underlies epileptogenesis. Major childhood epilepsies as medial temporal lobe epilepsy (MTLE), absence epilepsy (AE) and human perisylvian network (PN) epilepsies - made us good models to study. These conditions come from an epileptic transformation of the affected functional systems. This approach allows a system-based taxonomy instead of the outworn generalized-focal classification. MTLE links to the memory-system, where epileptic transformation results in a switch of normal sharp wave-ripples to epileptic spikes and pathological high frequency oscillations, compromising sleep-related memory consolidation. Absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) belong to the corticothalamic system. The burst-firing mode of NREM sleep normally producing sleep-spindles turns to an epileptic working mode ejecting bilateral synchronous spike-waves. There seems to be a progressive transition from AE to JME. Shared absences and similar bilateral synchronous discharges show the belonging of the two conditions, while the continuous age windows - AE affecting schoolchildren, JME the adolescents - and the increased excitability in JME compared to AE supports the notion of progression. In perisylvian network epilepsies - idiopathic focal childhood epilepsies and electrical status epilepticus in sleep including Landau-Kleffner syndrome - centrotemporal spikes turn epileptic, with the potential to cause cognitive impairment. Postinjury epilepsies modeled by the isolated cortex model highlight the shared way of epileptogenesis suggesting the derailment of NREM sleep-related homeostatic plasticity as a common step. NREM sleep provides templates for plasticity derailing to epileptic variants under proper conditions. This sleep-origin explains epileptiform discharges' link and similarity with NREM sleep slow oscillations, spindles and ripples. Normal synaptic plasticity erroneously overgrowing homeostatic processes may derail toward an epileptic working-mode manifesting the involved system's features. The impact of NREM sleep is unclear in epileptogenesis occurring in adolescence and adulthood, when plasticity is lower. The epileptic process interferes with homeostatic synaptic plasticity and may cause cognitive impairment. Its type and degree depends on the affected network's function. We hypothesize a vicious circle between sleep end epilepsy. The epileptic derailment of normal plasticity interferes with sleep cognitive functions. Sleep and epilepsy interconnect by the pathology of plasticity.

Neural Field Theory of Evoked Response Potentials With Attentional Gain Dynamics.

A generalized neural field model of large-scale activity in the corticothalamic system is used to predict standard evoked potentials. This model embodies local feedbacks that modulate the gains of neural activity as part of the response to incoming stimuli and thus enables both activity changes and effective connectivity changes to be calculated as parts of a generalized evoked response, and their relative contributions to be determined. The results show that incorporation of gain modulations enables a compact and physically justifiable description of the differences in gain between background-EEG and standard-ERP conditions, with the latter able to be initiated from the background state, rather than requiring distinct parameters as in earlier work. In particular, top-down gains are found to be reduced during an ERP, consistent with recent theoretical suggestions that the role of internal models is diminished in favor of external inputs when the latter change suddenly. The static-gain and modulated-gain system transfer functions are analyzed via control theory in terms of system resonances that were recently shown to implement data filtering whose gain adjustments can be interpreted as attention. These filters are shown to govern early and late features in standard evoked responses and their gain parameters are shown to be dynamically adjusted in a way that implements a form of attention. The results show that dynamically modulated resonant filters responsible for the low-frequency oscillations in an evoked potential response have different parameters than those responsible for low-frequency resting EEG responses, while both responses share similar mid- and high-frequency resonant filters. These results provide a biophysical mechanism by which oscillatory activity in the theta, alpha, and beta frequency ranges of an evoked response are modulated as reflections of attention; notably theta is enhanced and alpha suppressed during the latter parts of the ERP. Furthermore, the model enables the part of the ERP response induced by gain modulations to be estimated and interpreted in terms of attention.

Nonlinear wave-wave interactions in the brain

Neural field theory of the corticothalamic system is used to analyze nonlinear wave-wave interactions in steady state visual evoked potential responses. The nonlinear power spectrum is analytically calculated by convolving the linear power spectrum with itself and other factors. Periodic sine and square wave stimuli are used to generate steady state visual evoked potential responses and to study stimulus-driven nonlinear corticothalamic dynamic interactions. Moreover, we use dual sine drives to analyze the driven dynamics. Numerical analysis shows that the nonlinear power spectrum embodies key nonlinear features, including harmonic and subharmonic generation, entrainment of the alpha rhythm to periodic stimuli at the drive frequency, sum and difference frequencies due to wave-wave coalescence and decay. Further, the scaling properties of the key phenomena observed in nonlinear interactions are studied, verifying some of the theoretical predictions for these being generated by three-wave processes.

Effects of physiological parameter evolution on the dynamics of tonic-clonic seizures.

The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ∼ 10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ∼ 18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the time to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations is inversely proportional to the square root of the ramp rate.

Structural plasticity of GABAergic and glutamatergic networks in the motor thalamus of parkinsonian monkeys.

In the primate thalamus, the parvocellular ventral anterior nucleus (VApc) and the centromedian nucleus (CM) receive GABAergic projections from the internal globus pallidus (GPi) and glutamatergic inputs from motor cortices. In this study, we used electron microscopy to assess potential structural changes in GABAergic and glutamatergic microcircuits in the VApc and CM of MPTP-treated parkinsonian monkeys. The intensity of immunostaining for GABAergic markers in VApc and CM did not differ between control and parkinsonian monkeys. In the electron microscope, three major types of terminals were identified in both nuclei: (a) vesicular glutamate transporter 1 (vGluT1)-positive terminals forming asymmetric synapses (type As), which originate from the cerebral cortex, (b) GABAergic terminals forming single symmetric synapses (type S1), which likely arise from the reticular nucleus and GABAergic interneurons, and (c) GABAergic terminals forming multiple symmetric synapses (type S2), which originate from GPi. The density of As terminals outnumbered that of S1 and S2 terminals in VApc and CM of control and parkinsonian animals. No significant change was found in the abundance and synaptic connectivity of S1 and S2 terminals in VApc or CM of MPTP-treated monkeys, while the prevalence of "As" terminals in VApc of parkinsonian monkeys was 51.4% lower than in controls. The cross-sectional area of vGluT1-positive boutons in both VApc and CM of parkinsonian monkeys was significantly larger than in controls, but their pattern of innervation of thalamic cells was not altered. Our findings suggest that the corticothalamic system undergoes significant synaptic remodeling in the parkinsonian state.

Neural Field Theory of Corticothalamic Attention With Control System Analysis.

Neural field theory is used to analyze attention by extending an existing model of the large-scale activity in the corticothalamic system to incorporate local feedbacks that modulate the gains of neural connectivity as part of the response to incoming stimuli. Treatment of both activity changes and connectivity changes as part of a generalized response enables generalized linear transfer functions of the combined response to be derived. These are then analyzed and interpreted via control theory in terms of stimulus-driven changes in system resonances that were recently shown to implement data filtering and prediction of the inputs. Using simple visual stimuli as a test case, it is shown that the gain response can implement attention by evaluating two main features of the stimuli: the magnitude and the rate of change, by increasing the weight placed on the rate of change in response to sudden changes, while reducing the contribution of stimuli value in tandem. These changes of filter parameters are shown to improve the prediction of the upcoming stimuli based on its recent time course. This outcome is analogous to controller-parameter tuning for performance enhancement in engineering control theory.

Mode-locking dynamics of corticothalamic system responses to periodic external stimuli

A physiologically based continuum model of the corticothalamic system is applied to explore mode-locking dynamics of ongoing cortical activity subject to periodic drive. The ongoing cortical activity is poised near a Hopf bifurcation. Time-dependent center manifold reduction shows that the nonlinear dynamics of driven corticothalamic system with delays can be described by an inhomogeneous low-dimensional equation near the critical point of the Hopf bifurcation. This driven normal form captures the main features of experimentally observed nonlinear interactions between brain activity and periodic stimuli. The effects of underlying physiological parameters on the type of Hopf bifurcation and onset dynamics are then studied, which allows the determination of phase-locked structures for various regions in the parameter space of the drive. It is shown that the system can adjust its oscillation regime to the frequency content of stimuli. The key features of entrainment of the alpha rhythm to periodic stimuli, including harmonic and subharmonic generation, are also explored. The theoretical predictions of these nonlinear responses are confirmed by numerical simulations. Further, photosensitive seizures are predicted for physiologically based model parameters arising from mode locking to the frequency of periodic stimulus, and their harmonics due to higher order synchronization states. These results indicate that the approach used here provides a powerful framework for the study of nonlinear interactions between brain activity and flicker by incorporating periodic driving into the corticothalamic system.

Unified analysis of global and focal aspects of absence epilepsy via neural field theory of the corticothalamic system.

Absence epilepsy is characterized by a sudden paroxysmal loss of consciousness accompanied by oscillatory activity propagating over many brain areas. Although primary generalized absence seizures are supported by the global corticothalamic system, converging experimental evidence supports a focal theory of absence epilepsy. Here a physiology-based corticothalamic model is investigated with spatial heterogeneity due to focal epilepsy to unify global and focal aspects of absence epilepsy. Numeric and analytic calculations are employed to investigate the emergent spatiotemporal dynamics as well as their underlying dynamical mechanisms. They can be categorized into three scenarios: suppressed epilepsy, focal seizures, or generalized seizures, as summarized from a phase diagram vs focal width and characteristic axon range. The corresponding temporal frequencies and spatial extents of cortical waves in generalized seizures and focal seizures agree well with experimental observations of global and focal aspects of absence epilepsy, respectively. The emergence of the spatiotemporal dynamics corresponding to focal seizures provides a biophysical explanation of the temporally higher frequency but spatially more localized cortical waves observed in genetic rat models that display characteristics of human absence epilepsy. Predictions are also presented for further experimental test.

Unified dynamics of interictal events and absence seizures.

The dynamics of interictal events between absence seizures and their relationship to seizures themselves are investigated by employing a neural field model of the corticothalamic system. Interictal events are modeled as being due to transient parameter excursions beyond the seizure threshold, in the present case by sufficiently temporally varying the connection strength between the cerebral cortex and the thalamus. Increasing connection strength drives the system into ∼3-Hz seizure oscillations via a supercritical Hopf bifurcation once the linear instability threshold is passed. Depending on the time course of the excursion above threshold, different interictal activity event dynamics are seen in the time series of corticothalamic fields. These resemble experimental interictal time series observed via electroencephalography. It is found that the morphology of these events depends on the magnitude and duration of the excursion above threshold. For a large-amplitude excursion of short duration, events resemble interictal spikes, where one large spike is seen, followed by small damped oscillations. For a short excursion with long duration, events like observed interictal periodic sharp waves are seen. When both amplitude and duration above threshold are large, seizure oscillations are seen. Using these outcomes, proximity to seizure can be estimated and tracked.

Neural field theory of evoked response potentials in a spherical brain geometry.

Evoked response potentials (ERPs) are calculated in spherical and planar geometries using neural field theory of the corticothalamic system. The ERP is modeled as an impulse response and the resulting modal effects of spherical corticothalamic dynamics are explored, showing that results for spherical and planar geometries converge in the limit of large brain size. Cortical modal effects can lead to a double-peak structure in the ERP time series. It is found that the main difference between infinite planar geometry and spherical geometry is that the ERP peak is sharper and stronger in the spherical geometry. It is also found that the magnitude of the response decreases with increasing spatial width of the stimulus at the cortex. The peak is slightly delayed at large angles from the stimulus point, corresponding to group velocities of 6-10m s^{-1}. Strong modal effects are found in the spherical geometry, with the lowest few modes sufficing to describe the main features of ERPs, except very near to spatially narrow stimuli.

Fractal dimension analysis of states of consciousness and unconsciousness using transcranial magnetic stimulation

Background and objectiveKnowing whether a subject is conscious or not is a current challenge with a deep potential clinical impact. Recent theoretical considerations suggest that consciousness is linked to the complexity of distributed interactions within the corticothalamic system. The fractal dimension (FD) is a quantitative parameter that has been extensively used to analyse the complexity of structural and functional patterns of the human brain. In this study we investigate FD to assess whether it can discriminate between consciousness and different states of unconsciousness in healthy individuals. MethodsWe study 69 high-density electroencephalogram (hd-EEG) measurements after transcranial magnetic stimulation (TMS) in 18 healthy subjects progressing from wakefulness to non-rapid eye movement (NREM) sleep and sedation induced by different anaesthetic agents (xenon and propofol). We quantify the integration of thalamocortical networks by calculating the FD of a spatiotemporal voxelization obtained from the locations of all sources that are significantly activated by the perturbation (4DFD). Moreover, we study the temporal evolution of the evoked spatial distributions and compute a measure of the differentiation of the response by means of the Higuchi FD (HFD). Finally, a Fractal Dimension Index (FDI) of perturbational complexity is computed as the product of both quantities: integration FD (4DFD) and differentiation FD (HFD). ResultsWe found that FDI is significantly lower in sleep and sedation when compared to wakefulness and provides an almost perfect intra-subject discrimination between conscious and unconscious states. ConclusionsThese results support the combination of FD measures of cortical integration and cortical differentiation as a novel paradigm of tracking complex spatiotemporal dynamics in the brain that could provide further insights into the link between complexity and the brain's capacity to sustain consciousness.