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

An Unpredictable Brain Is a Conscious, Responsive Brain

Severe traumatic brain injuries typically result in loss of consciousness or coma. In deeply comatose patients with traumatic brain injury, cortical dynamics become simple, repetitive, and predictable. We review evidence that this low-complexity, high-predictability state results from a passive cortical state, represented by a stable repetitive attractor, that hinders the flexible formation of neuronal ensembles necessary for conscious experience. Our data and those from other groups support the hypothesis that this cortical passive state is because of the loss of thalamocortical input. We identify the unpredictability and complexity of cortical dynamics captured by local field potential as a sign of recovery from this passive coma attractor. In this Perspective article, we discuss how these electrophysiological biomarkers of the recovery of consciousness could inform the design of closed-loop stimulation paradigms to treat disorders of consciousness.

Seizing the Future: Predicting Epilepsy After TBI

ECoG Spiking Activity and Signal Dimension Are Early Predictive Measures of Epileptogenesis in a Translational Mouse Model of Traumatic Brain Injury Di Sapia R, Rizzi M, Moro F, Lisi I, Caccamo A, Ravizza T, Vezzani A, Zanier ER. Neurobiol Dis . 2023;185:106251. PMID: 37536383 . doi:10.1016/j.nbd.2023.106251 The latency between traumatic brain injury (TBI) and the onset of epilepsy (PTE) represents an opportunity for counteracting epileptogenesis. Antiepileptogenesis trials are hampered by the lack of sensitive biomarkers that allow to enrich patient’s population at-risk for PTE. We aimed to assess whether specific ECoG signals predict PTE in a clinically relevant mouse model with ∼60% epilepsy incidence. TBI was provoked in adult CD1 male mice by controlled cortical impact on the left parieto-temporal cortex, then mice were implanted with two perilesional cortical screw electrodes and two similar electrodes in the hemisphere contralateral to the lesion site. Acute seizures and spikes/sharp waves were ECoG-recorded during 1 week post-TBI. These early ECoG events were analyzed according to PTE incidence as assessed by measuring spontaneous recurrent seizures (SRS) at 5 months post-TBI. We found that incidence, number and duration of acute seizures during 3 days post-TBI were similar in PTE mice and mice not developing epilepsy (No SRS mice). Control mice with cortical electrodes (naïve, n = 5) or with electrodes and craniotomy (sham, n = 5) exhibited acute seizures but did not develop epilepsy. The daily number of spikes/sharp waves at the perilesional electrodes was increased similarly in PTE (n = 15) and No SRS (n = 8) mice vs controls (p < 0.05, n = 10) from day 2 post-injury. Differently, the daily number of spikes/sharp waves at both contralateral electrodes showed a progressive increase in PTE mice vs No SRS and control mice. In particular, spikes number was higher in PTE vs No SRS mice (p < 0.05) at 6 and 7 days post-TBI, and this measure predicted epilepsy development with high accuracy (AUC = 0.77, p = 0.03; CI 0.5830-0.9670). The cut-off value was validated in an independent cohort of TBI mice (n = 12). The daily spike number at the contralateral electrodes showed a circadian distribution in PTE mice which was not observed in No SRS mice. Analysis of non-linear dynamics at each electrode site showed changes in dimensionality during 4 days post-TBI. This measure yielded the best discrimination between PTE and No SRS mice (p < 0.01) at the cortical electrodes contralateral to injury. Data show that epileptiform activity contralateral to the lesion site has the highest predictive value for PTE in this model reinforcing the hypothesis that the hemisphere contralateral to the lesion core may drive epileptogenic networks after TBI.

Stationary stable cross-correlation pattern and task specific deviations in unresponsive wakefulness syndrome as well as clinically healthy subjects

Brain dynamics is highly non-stationary, permanently subject to ever-changing external conditions and continuously monitoring and adjusting internal control mechanisms. Finding stationary structures in this system, as has been done recently, is therefore of great importance for understanding fundamental dynamic trade relationships. Here we analyse electroencephalographic recordings (EEG) of 13 subjects with unresponsive wakefulness syndrome (UWS) during rest and while being influenced by different acoustic stimuli. We compare the results with a control group under the same experimental conditions and with clinically healthy subjects during overnight sleep. The main objective of this study is to investigate whether a stationary correlation pattern is also present in the UWS group, and if so, to what extent this structure resembles the one found in healthy subjects. Furthermore, we extract transient dynamical features via specific deviations from the stationary interrelation pattern. We find that (i) the UWS group is more heterogeneous than the two groups of healthy subjects, (ii) also the EEGs of the UWS group contain a stationary cross-correlation pattern, although it is less pronounced and shows less similarity to that found for healthy subjects and (iii) deviations from the stationary pattern are notably larger for the UWS than for the two groups of healthy subjects. The results suggest that the nervous system of subjects with UWS receive external stimuli but show an overreaching reaction to them, which may disturb opportune information processing.

Multi-modal MRI of hippocampal morphometry and connectivity after pediatric severe TBI

This investigation explores memory performance using the California Verbal Learning Test in relation to morphometric and connectivity measures of the memory network in severe traumatic brain injury. Twenty-two adolescents with severe traumatic brain injury were recruited for multimodal MRI scanning 1-2 years post-injury at 13 participating sites. Analyses included hippocampal volume derived from anatomical T1-weighted imaging, fornix white matter microstructure from diffusion tensor imaging, and hippocampal resting-state functional magnetic resonance imaging connectivity as well as diffusion-based structural connectivity. A typically developing control cohort of forty-nine age-matched children also underwent scanning and neurocognitive assessment. Results showed hippocampus volume was decreased in traumatic brain injury with respect to controls. Further, hippocampal volume loss was associated with worse performance on memory and learning in traumatic brain injury subjects. Similarly, hippocampal fornix fractional anisotropy was reduced in traumatic brain injury with respect to controls, while decreased fractional anisotropy in the hippocampal fornix also was associated with worse performance on memory and learning in traumatic brain injury subjects. Additionally, reduced structural connectivity of left hippocampus to thalamus and calcarine sulcus was associated with memory and learning in traumatic brain injury subjects. Functional connectivity in the left hippocampal network was also associated with memory and learning in traumatic brain injury subjects. These regional findings from a multi-modal neuroimaging approach should not only be useful for gaining valuable insight into traumatic brain injury induced memory and learning disfunction, but may also be informative for monitoring injury progression, recovery, and for developing rehabilitation as well as therapy strategies.

Propofol-mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy

A critical component of anesthesia is the loss of sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of nonhuman primates before and during propofol-mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-related synchronization between brain areas in the local field potential of Awake animals. By contrast, propofol-mediated unconsciousness eliminated stimulus-related synchrony and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in Awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofol's effect on sensory processing is not just because of asynchronous Down states. Rather, both Down states and Up states reflect disrupted dynamics.

ECoG spiking activity and signal dimension are early predictive measures of epileptogenesis in a translational mouse model of traumatic brain injury

The latency between traumatic brain injury (TBI) and the onset of epilepsy (PTE) represents an opportunity for counteracting epileptogenesis. Antiepileptogenesis trials are hampered by the lack of sensitive biomarkers that allow to enrich patient's population at-risk for PTE. We aimed to assess whether specific ECoG signals predict PTE in a clinically relevant mouse model with ∼60% epilepsy incidence. TBI was provoked in adult CD1 male mice by controlled cortical impact on the left parieto-temporal cortex, then mice were implanted with two perilesional cortical screw electrodes and two similar electrodes in the hemisphere contralateral to the lesion site. Acute seizures and spikes/sharp waves were ECoG-recorded during 1 week post-TBI. These early ECoG events were analyzed according to PTE incidence as assessed by measuring spontaneous recurrent seizures (SRS) at 5 months post-TBI. We found that incidence, number and duration of acute seizures during 3 days post-TBI were similar in PTE mice and mice not developing epilepsy (No SRS mice). Control mice with cortical electrodes (naïve, n = 5) or with electrodes and craniotomy (sham, n = 5) exhibited acute seizures but did not develop epilepsy. The daily number of spikes/sharp waves at the perilesional electrodes was increased similarly in PTE (n = 15) and No SRS (n = 8) mice vs controls (p < 0.05, n = 10) from day 2 post-injury. Differently, the daily number of spikes/sharp waves at both contralateral electrodes showed a progressive increase in PTE mice vs No SRS and control mice. In particular, spikes number was higher in PTE vs No SRS mice (p < 0.05) at 6 and 7 days post-TBI, and this measure predicted epilepsy development with high accuracy (AUC = 0.77, p = 0.03; CI 0.5830-0.9670). The cut-off value was validated in an independent cohort of TBI mice (n = 12). The daily spike number at the contralateral electrodes showed a circadian distribution in PTE mice which was not observed in No SRS mice. Analysis of non-linear dynamics at each electrode site showed changes in dimensionality during 4 days post-TBI. This measure yielded the best discrimination between PTE and No SRS mice (p < 0.01) at the cortical electrodes contralateral to injury. Data show that epileptiform activity contralateral to the lesion site has the the highest predictive value for PTE in this model reinforcing the hypothesis that the hemisphere contralateral to the lesion core may drive epileptogenic networks after TBI.

Thalamocortical Coherence Predicts Persistent Postconcussive Symptoms

The pathogenetic mechanism of persistent post-concussive symptoms (PCS) following concussion remains unclear. Thalamic damage is known to play a role in PCS prolongation while the evidence and biomarkers that trigger persistent PCS have never been elucidated. We collected longitudinal neuroimaging and behavior data from patients and rodents after concussion, complemented with rodents' histological staining data, to unravel the early biomarkers of persistent PCS. Diffusion tensor imaging (DTI) were acquired to investigated the thalamic damage, while quantitative thalamocortical coherence was derived through resting-state functional MRI for evaluating thalamocortical functioning and predicting long-term behavioral outcome. Patients with prolonged symptoms showed abnormal DTI-derived indices at the boundaries of bilateral thalami (peri-thalamic regions). Both patients and rats with persistent symptoms demonstrated enhanced thalamocortical coherence between different thalamocortical circuits, which disrupted thalamocortical multifunctionality. In rodents, the persistent DTI abnormalities were validated in thalamic reticular nucleus (TRN) through immunohistochemistry, and correlated with enhanced thalamocortical coherence. Strong predictive power of these coherence biomarkers for long-term PCS was also validated using another patient cohort. Postconcussive events may begin with persistent TRN injury, followed by disrupted thalamocortical coherence and prolonged PCS. Functional MRI-based coherence measures can be surrogate biomarkers for early prediction of long-term PCS.

Microscale multicircuit brain stimulation: Achieving real-time brain state control for novel applications

Neurological and psychiatric disorders typically result from dysfunction across multiple neural circuits. Most of these disorders lack a satisfactory neuromodulation treatment. However, deep brain stimulation (DBS) has been successful in a limited number of disorders; DBS typically targets one or two brain areas with single contacts on relatively large electrodes, allowing for only coarse modulation of circuit function. Because of the dysfunction in distributed neural circuits - each requiring fine, tailored modulation - that characterizes most neuropsychiatric disorders, this approach holds limited promise. To develop the next generation of neuromodulation therapies, we will have to achieve fine-grained, closed-loop control over multiple neural circuits. Recent work has demonstrated spatial and frequency selectivity using microstimulation with many small, closely-spaced contacts, mimicking endogenous neural dynamics. Using custom electrode design and stimulation parameters, it should be possible to achieve bidirectional control over behavioral outcomes, such as increasing or decreasing arousal during central thalamic stimulation. Here, we discuss one possible approach, which we term microscale multicircuit brain stimulation (MMBS). We discuss how machine learning leverages behavioral and neural data to find optimal stimulation parameters across multiple contacts, to drive the brain towards desired states associated with behavioral goals. We expound a mathematical framework for MMBS, where behavioral and neural responses adjust the model in real-time, allowing us to adjust stimulation in real-time. These technologies will be critical to the development of the next generation of neurostimulation therapies, which will allow us to treat problems like disorders of consciousness and cognition.

Cortical recordings reveal hidden early signs of recovery following traumatic brain injury: A case report

Prognosticating recovery of consciousness after severe traumatic brain injury (TBI) is a difficult task. Understanding the mechanism of recovery of consciousness in these patients will undoubtedly help clarify this issue. Recent research has underscored the importance of electrophysiological data in characterizing the state of the brain during this period of unconsciousness. Here, we investigated cortical electrophysiological recordings from a single TBI patient and discovered that high-frequency activity associated with the return of consciousness reappeared in a spatiotemporal fashion. We observed a shift toward higher frequencies first in the anterior cingulate cortex, and then later in the dorsolateral prefrontal cortex. This finding suggests that recovery may originate in more internal cortices and progress to superficial ones. Although this observation occurred in a single patient, it points to a potential mechanism for recovery of normal cortical activity in the return of consciousness following TBI.

Thalamo-Prefrontal Connectivity Correlates With Early Command-Following After Severe Traumatic Brain Injury

Recovery of consciousness after traumatic brain injury (TBI) is heterogeneous and difficult to predict. Structures such as the thalamus and prefrontal cortex are thought to be important in facilitating consciousness. We sought to investigate whether the integrity of thalamo-prefrontal circuits, assessed via diffusion tensor imaging (DTI), was associated with the return of goal-directed behavior after severe TBI. We classified a cohort of severe TBI patients (N = 25, 20 males) into Early and Late/Never outcome groups based on their ability to follow commands within 30 days post-injury. We assessed connectivity between whole thalamus, and mediodorsal thalamus (MD), to prefrontal cortex (PFC) subregions including dorsolateral PFC (dlPFC), medial PFC (mPFC), anterior cingulate (ACC), and orbitofrontal (OFC) cortices. We found that the integrity of thalamic projections to PFC subregions (L OFC, L and R ACC, and R mPFC) was significantly associated with Early command-following. This association persisted when the analysis was restricted to prefrontal-mediodorsal (MD) thalamus connectivity. In contrast, dlPFC connectivity to thalamus was not significantly associated with command-following. Using the integrity of thalamo-prefrontal connections, we created a linear regression model that demonstrated 72% accuracy in predicting command-following after a leave-one-out analysis. Together, these data support a role for thalamo-prefrontal connectivity in the return of goal-directed behavior following TBI.