Multiscale effects of excitatory-inhibitory homeostasis in lesioned cortical networks: A computational study.

Stroke-related disruptions in functional connectivity (FC) often spread beyond lesioned areas and, given the localized nature of lesions, it is unclear how the recovery of FC is orchestrated on a global scale. Since recovery is accompanied by long-term changes in excitability, we propose excitatory-inhibitory (E-I) homeostasis as a driving mechanism. We present a large-scale model of the neocortex, with synaptic scaling of local inhibition, showing how E-I homeostasis can drive the post-lesion restoration of FC and linking it to changes in excitability. We show that functional networks could reorganize to recover disrupted modularity and small-worldness, but not network dynamics, suggesting the need to consider forms of plasticity beyond synaptic scaling of inhibition. On average, we observed widespread increases in excitability, with the emergence of complex lesion-dependent patterns related to biomarkers of relevant side effects of stroke, such as epilepsy, depression and chronic pain. In summary, our results show that the effects of E-I homeostasis extend beyond local E-I balance, driving the restoration of global properties of FC, and relating to post-stroke symptomatology. Therefore, we suggest the framework of E-I homeostasis as a relevant theoretical foundation for the study of stroke recovery and for understanding the emergence of meaningful features of FC from local dynamics.

Volitional learning promotes theta phase coding in the human hippocampus.

Electrophysiological studies in rodents show that active navigation enhances hippocampal theta oscillations (4-12 Hz), providing a temporal framework for stimulus-related neural codes. Here we show that active learning promotes a similar phase coding regime in humans, although in a lower frequency range (3-8 Hz). We analyzed intracranial electroencephalography (iEEG) from epilepsy patients who studied images under either volitional or passive learning conditions. Active learning increased memory performance and hippocampal theta oscillations and promoted a more accurate reactivation of stimulus-specific information during memory retrieval. Representational signals were clustered to opposite phases of the theta cycle during encoding and retrieval. Critically, during active but not passive learning, the temporal structure of intracycle reactivations in theta reflected the semantic similarity of stimuli, segregating conceptually similar items into more distant theta phases. Taken together, these results demonstrate a multilayered mechanism by which active learning improves memory via a phylogenetically old phase coding scheme.

Saccade rate is associated with recall of items in working memory.

Working memory has been shown to rely on theta oscillations' phase synchronicity for item encoding and recall. At the same time, saccadic eye movements during visual exploration have been observed to trigger theta-phase resets, raising the question of whether the neuronal substrates of mnemonic processing rely on motor-evoked responses. To quantify the relationship between saccades and working memory load, we recorded eye tracking and behavioral data from human participants simultaneously performing an n-back Sternberg auditory task and a hue-based catch detection task. In addition to task-specific interference in performance, we also found that saccade rate was modulated by working memory load in the Sternberg task's preresponse stage. Our results support the possibility of interplay between saccades and hippocampal theta during working memory retrieval of items.

Rehabilitation Gaming System for Alcohol-Related Cognitive Impairment: A Pilot Usability Study.

AIMS: Cognitive impairment in patients with alcohol use disorder (AUD) is highly prevalent, and it negatively impacts treatment outcome. However, this condition is neither systematically assessed nor treated. Thus, we aimed to explore the usability of a virtual reality-based protocol ('Rehabilitation Gaming System', RGS) for patients with AUD. METHODS: Twenty AUD patients (50% also cognitive impairment) underwent a single session of the RGS protocol (four cognitive training tasks, 10 minutes each). System Usability Scale (SUS) and Post-Study System Usability Questionnaire (PSSUQ) were applied to assess the RGS usability and patients' satisfaction with it. Also, the Perceived Competence Scale was administered to assess the patients' feelings of competence when using the training protocol. Comparisons of the responses to these questionnaires were performed between AUD patients with cognitive impairment and those without cognitive impairment. RESULTS: RGS usability was very positively rated (median SUS score = 80, Interquartile Range, IQR = 68.13-86-88). No significant differences were found in the median SUS scores for any of the sociodemographic or clinical variables, excepting for gender (women median score = 85; IQR = 80-94.38 vs. men median score = 71.25; IQR = 61.25-89.25; P-value = 0.035). The quality of the information provided by the RGS training scenarios and the usability were positively rated (PSSUQ), and patients experienced high feelings of competence. CONCLUSIONS: The RGS has been found to be usable in the short term and patients with AUD stated to be satisfied with it. Future larger, randomized trials are needed to explore the effectiveness of this tool to help overcome the cognitive deficits in AUD patients.

Estimating upper-extremity function from kinematics in stroke patients following goal-oriented computer-based training.

INTRODUCTION: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. METHODS: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. RESULTS: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of [Formula: see text]: 0.38 with an error ([Formula: see text]: 12.8). Next, we evaluate its reliability ([Formula: see text] for test-retest), longitudinal external validity ([Formula: see text] true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements ([Formula: see text]: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory ([Formula: see text]: 0.40) and Barthel Index ([Formula: see text]: 0.35). CONCLUSIONS: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

Adaptive conjunctive cognitive training (ACCT) in virtual reality for chronic stroke patients: a randomized controlled pilot trial.

BACKGROUND: Current evidence for the effectiveness of post-stroke cognitive rehabilitation is weak, possibly due to two reasons. First, patients typically express cognitive deficits in several domains. Therapies focusing on specific cognitive deficits might not address their interrelated neurological nature. Second, co-occurring psychological problems are often neglected or not diagnosed, although post-stroke depression is common and related to cognitive deficits. This pilot trial aims to test a rehabilitation program in virtual reality that trains various cognitive domains in conjunction, by adapting to the patient's disability and while investigating the influence of comorbidities. METHODS: Thirty community-dwelling stroke patients at the chronic stage and suffering from cognitive impairment performed 30 min of daily training for 6 weeks. The experimental group followed, so called, adaptive conjunctive cognitive training (ACCT) using RGS, whereas the control group solved standard cognitive tasks at home for an equivalent amount of time. A comprehensive test battery covering executive function, spatial awareness, attention, and memory as well as independence, depression, and motor impairment was applied at baseline, at 6 weeks and 18-weeks follow-up. RESULTS: At baseline, 75% of our sample had an impairment in more than one cognitive domain. The experimental group showed improvements in attention ([Formula: see text] (2) = 9.57, p < .01), spatial awareness ([Formula: see text] (2) = 11.23, p < .01) and generalized cognitive functioning ([Formula: see text] (2) = 15.5, p < .001). No significant change was seen in the executive function and memory domain. For the control group, no significant change over time was found. Further, they worsened in their depression level after treatment (T = 45, r = .72, p < .01) but returned to baseline at follow-up. The experimental group displayed a lower level of depression than the control group after treatment (Ws = 81.5, z = - 2.76, r = - .60, p < .01) and (Ws = 92, z = - 2.03, r = - .44, p < .05). CONCLUSIONS: ACCT positively influences attention and spatial awareness, as well as depressive mood in chronic stroke patients. TRIAL REGISTRATION: The trial was registered prospectively at ClinicalTrials.gov (NCT02816008) on June 21, 2016.

Multisensory cueing facilitates naming in aphasia.

BACKGROUND: Impaired naming is a ubiquitous symptom in all types of aphasia, which often adversely impacts independence, quality of life, and recovery of affected individuals. Previous research has demonstrated that naming can be facilitated by phonological and semantic cueing strategies that are largely incorporated into the treatment of anomic disturbances. Beneficial effects of cueing, whereby naming becomes faster and more accurate, are often attributed to the priming mechanisms occurring within the distributed language network. OBJECTIVE: We proposed and explored two novel cueing techniques: (1) Silent Visuomotor Cues (SVC), which provided articulatory information of target words presented in the form of silent videos, and (2) Semantic Auditory Cues (SAC), which consisted of acoustic information semantically relevant to target words (ringing for "telephone"). Grounded in neurophysiological evidence, we hypothesized that both SVC and SAC might aid communicative effectiveness possibly by triggering activity in perceptual and semantic language regions, respectively. METHODS: Ten participants with chronic non-fluent aphasia were recruited for a longitudinal clinical intervention. Participants were split into dyads (i.e., five pairs of two participants) and required to engage in a turn-based peer-to-peer language game using the Rehabilitation Gaming System for aphasia (RGSa). The objective of the RGSa sessions was to practice communicative acts, such as making a request. We administered SVCs and SACs in a pseudorandomized manner at the moment when the active player selected the object to be requested from the interlocutor. For the analysis, we compared the times from selection to the reception of the desired object between cued and non-cued trials. RESULTS: Naming accuracy, as measured by a standard clinical scale, significantly improved for all stimuli at each evaluation point, including the follow-up. Moreover, the results yielded beneficial effects of both SVC and SAC cues on word naming, especially at the early intervention sessions when the exposure to the target lexicon was infrequent. CONCLUSIONS: This study supports the efficacy of the proposed cueing strategies which could be integrated into the clinic or mobile technology to aid naming even at the chronic stages of aphasia. These findings are consistent with sensorimotor accounts of language processing, suggesting a coupling between language, motor, and semantic brain regions. TRIAL REGISTRATION: NCT02928822 . Registered 30 May 2016.

A critical time window for recovery extends beyond one-year post-stroke.

The impact of rehabilitation on post-stroke motor recovery and its dependency on the patient's chronicity remain unclear. The field has widely accepted the notion of a proportional recovery rule with a "critical window for recovery" within the first 3-6 mo poststroke. This hypothesis justifies the general cessation of physical therapy at chronic stages. However, the limits of this critical window have, so far, been poorly defined. In this analysis, we address this question, and we further explore the temporal structure of motor recovery using individual patient data from a homogeneous sample of 219 individuals with mild to moderate upper-limb hemiparesis. We observed that improvement in body function and structure was possible even at late chronic stages. A bootstrapping analysis revealed a gradient of enhanced sensitivity to treatment that extended beyond 12 mo poststroke. Clinical guidelines for rehabilitation should be revised in the context of this temporal structure. NEW & NOTEWORTHY Previous studies in humans suggest that there is a 3- to 6-mo "critical window" of heightened neuroplasticity poststroke. We analyze the temporal structure of recovery in patients with hemiparesis and uncover a precise gradient of enhanced sensitivity to treatment that expands far beyond the limits of the so-called critical window. These findings highlight the need for providing therapy to patients at the chronic and late chronic stages.

Long-term spatial clustering in free recall.

We explored the influence of space on the organisation of items in long-term memory. In two experiments, we asked our participants to explore a virtual environment and memorise discrete items presented at specific locations. Memory for those items was later on tested in immediate (T1) and 24 hours delayed (T2) free recall tests, in which subjects were asked to recall as many items as possible in any order. In experiment 2, we further examined the contribution of active and passive navigation in recollection dynamics. Results across experiments revealed a significant tendency for participants to consecutively recall items that were encountered in proximate locations during learning. Moreover, the degree of spatial organisation and the total number of items recalled were positively correlated in the immediate and the delayed tests. Results from experiment 2 indicated that the spatial clustering of items was independent of navigation types. Our results highlight the long-term stability of spatial clustering effects and their correlation with recall performance, complementing previous results collected in immediate or briefly delayed tests.

The perceptual shaping of anticipatory actions.

Humans display anticipatory motor responses to minimize the adverse effects of predictable perturbations. A widely accepted explanation for this behaviour relies on the notion of an inverse model that, learning from motor errors, anticipates corrective responses. Here, we propose and validate the alternative hypothesis that anticipatory control can be realized through a cascade of purely sensory predictions that drive the motor system, reflecting the causal sequence of the perceptual events preceding the error. We compare both hypotheses in a simulated anticipatory postural adjustment task. We observe that adaptation in the sensory domain, but not in the motor one, supports the robust and generalizable anticipatory control characteristic of biological systems. Our proposal unites the neurobiology of the cerebellum with the theory of active inference and provides a concrete implementation of its core tenets with great relevance both to our understanding of biological control systems and, possibly, to their emulation in complex artefacts.

Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex.

Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear. This consensus paper gathers diverse recent views on a variety of important roles played by the cerebellum within the cerebello-basal ganglia-thalamo-cortical system across a range of motor and cognitive functions. The paper includes theoretical and empirical contributions, which cover the following topics: recent evidence supporting the dynamical interplay between cerebellum, basal ganglia, and cortical areas in humans and other animals; theoretical neuroscience perspectives and empirical evidence on the reciprocal influences between cerebellum, basal ganglia, and cortex in learning and control processes; and data suggesting possible roles of the cerebellum in basal ganglia movement disorders. Although starting from different backgrounds and dealing with different topics, all the contributors agree that viewing the cerebellum, basal ganglia, and cortex as an integrated system enables us to understand the function of these areas in radically different ways. In addition, there is unanimous consensus between the authors that future experimental and computational work is needed to understand the function of cerebellar-basal ganglia circuitry in both motor and non-motor functions. The paper reports the most advanced perspectives on the role of the cerebellum within the cerebello-basal ganglia-thalamo-cortical system and illustrates other elements of consensus as well as disagreements and open questions in the field.

The Impact of Cortical Lesions on Thalamo-Cortical Network Dynamics after Acute Ischaemic Stroke: A Combined Experimental and Theoretical Study.

The neocortex and thalamus provide a core substrate for perception, cognition, and action, and are interconnected through different direct and indirect pathways that maintain specific dynamics associated with functional states including wakefulness and sleep. It has been shown that a lack of excitation, or enhanced subcortical inhibition, can disrupt this system and drive thalamic nuclei into an attractor state of low-frequency bursting and further entrainment of thalamo-cortical circuits, also called thalamo-cortical dysrhythmia (TCD). The question remains however whether similar TCD-like phenomena can arise with a cortical origin. For instance, in stroke, a cortical lesion could disrupt thalamo-cortical interactions through an attenuation of the excitatory drive onto the thalamus, creating an imbalance between excitation and inhibition that can lead to a state of TCD. Here we tested this hypothesis by comparing the resting-state EEG recordings of acute ischaemic stroke patients (N = 21) with those of healthy, age-matched control-subjects (N = 17). We observed that these patients displayed the hallmarks of TCD: a characteristic downward shift of dominant α-peaks in the EEG power spectra, together with increased power over the lower frequencies (δ and θ-range). Contrary to general observations in TCD, the patients also displayed a broad reduction in ß-band activity. In order to explain the genesis of this stroke-induced TCD, we developed a biologically constrained model of a general thalamo-cortical module, allowing us to identify the specific cellular and network mechanisms involved. Our model showed that a lesion in the cortical component leads to sustained cell membrane hyperpolarization in the corresponding thalamic relay neurons, that in turn leads to the de-inactivation of voltage-gated T-type Ca2+-channels, switching neurons from tonic spiking to a pathological bursting regime. This thalamic bursting synchronises activity on a population level through divergent intrathalamic circuits, and entrains thalamo-cortical pathways by means of propagating low-frequency oscillations beyond the restricted region of the lesion. Hence, pathological stroke-induced thalamo-cortical dynamics can be the source of diaschisis, and account for the dissociation between lesion location and non-specific symptoms of stroke such as neuropathic pain and hemispatial neglect.

A signature of attractor dynamics in the CA3 region of the hippocampus.

The notion of attractor networks is the leading hypothesis for how associative memories are stored and recalled. A defining anatomical feature of such networks is excitatory recurrent connections. These "attract" the firing pattern of the network to a stored pattern, even when the external input is incomplete (pattern completion). The CA3 region of the hippocampus has been postulated to be such an attractor network; however, the experimental evidence has been ambiguous, leading to the suggestion that CA3 is not an attractor network. In order to resolve this controversy and to better understand how CA3 functions, we simulated CA3 and its input structures. In our simulation, we could reproduce critical experimental results and establish the criteria for identifying attractor properties. Notably, under conditions in which there is continuous input, the output should be "attracted" to a stored pattern. However, contrary to previous expectations, as a pattern is gradually "morphed" from one stored pattern to another, a sharp transition between output patterns is not expected. The observed firing patterns of CA3 meet these criteria and can be quantitatively accounted for by our model. Notably, as morphing proceeds, the activity pattern in the dentate gyrus changes; in contrast, the activity pattern in the downstream CA3 network is attracted to a stored pattern and thus undergoes little change. We furthermore show that other aspects of the observed firing patterns can be explained by learning that occurs during behavioral testing. The CA3 thus displays both the learning and recall signatures of an attractor network. These observations, taken together with existing anatomical and behavioral evidence, make the strong case that CA3 constructs associative memories based on attractor dynamics.

Socially adaptive cognitive architecture for human-robot collaboration in industrial settings.

This paper introduces DAC-HRC, a novel cognitive architecture designed to optimize human-robot collaboration (HRC) in industrial settings, particularly within the context of Industry 4.0. The architecture is grounded in the Distributed Adaptive Control theory and the principles of joint intentionality and interdependence, which are key to effective HRC. Joint intentionality refers to the shared goals and mutual understanding between a human and a robot, while interdependence emphasizes the reliance on each other's capabilities to complete tasks. DAC-HRC is applied to a hybrid recycling plant for the disassembly and recycling of Waste Electrical and Electronic Equipment (WEEE) devices. The architecture incorporates several cognitive modules operating at different timescales and abstraction levels, fostering adaptive collaboration that is personalized to each human user. The effectiveness of DAC-HRC is demonstrated through several pilot studies, showcasing functionalities such as turn-taking interaction, personalized error-handling mechanisms, adaptive safety measures, and gesture-based communication. These features enhance human-robot collaboration in the recycling plant by promoting real-time robot adaptation to human needs and preferences. The DAC-HRC architecture aims to contribute to the development of a new HRC paradigm by paving the way for more seamless and efficient collaboration in Industry 4.0 by relying on socially adept cognitive architectures.

Redefining stroke rehabilitation: Mobilizing the embodied goal-oriented brain.

Advancements in stroke rehabilitation remain limited and call for a reorientation. Based on recent results, this study proposes a network-centric perspective on stroke, positing that it not only causes localized deficits but also affects the brain's intricate network of networks, transiting it into a pathological state. Translating these system-level insights into interventions requires brain theory, and the Distributed Adaptive Control (DAC) theory offers such a framework. When applied in the rehabilitation gaming system, these principles demonstrate superior results over conventional methods. This impact stems from activating extensive brain networks, particularly the executive control network, focused motor learning, and maintaining excitatory-inhibitory balance, which is essential for neural repair and functional reorganization. The analysis stresses uniting preclinical and clinical research and placing the architecture of the embodied volitional brain at the centre of rehabilitation approaches.

Patient-specific modeling for guided rehabilitation of stroke patients: the BrainX3 use-case.

BrainX3 is an interactive neuroinformatics platform that has been thoughtfully designed to support neuroscientists and clinicians with the visualization, analysis, and simulation of human neuroimaging, electrophysiological data, and brain models. The platform is intended to facilitate research and clinical use cases, with a focus on personalized medicine diagnostics, prognostics, and intervention decisions. BrainX3 is designed to provide an intuitive user experience and is equipped to handle different data types and 3D visualizations. To enhance patient-based analysis, and in keeping with the principles of personalized medicine, we propose a framework that can assist clinicians in identifying lesions and making patient-specific intervention decisions. To this end, we are developing an AI-based model for lesion identification, along with a mapping of tract information. By leveraging the patient's lesion information, we can gain valuable insights into the structural damage caused by the lesion. Furthermore, constraining whole-brain models with patient-specific disconnection masks can allow for the detection of mesoscale excitatory-inhibitory imbalances that cause disruptions in macroscale network properties. Finally, such information has the potential to guide neuromodulation approaches, assisting in the choice of candidate targets for stimulation techniques such as Transcranial Ultrasound Stimulation (TUS), which modulate E-I balance, potentiating cortical reorganization and the restoration of the dynamics and functionality disrupted due to the lesion.

The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke.

BACKGROUND AND PURPOSE: Although there is strong evidence on the beneficial effects of virtual reality (VR)-based rehabilitation, it is not yet well understood how the different aspects of these systems affect recovery. Consequently, we do not exactly know what features of VR neurorehabilitation systems are decisive in conveying their beneficial effects. METHODS: To specifically address this issue, we developed 3 different configurations of the same VR-based rehabilitation system, the Rehabilitation Gaming System, using 3 different interface technologies: vision-based tracking, haptics, and a passive exoskeleton. Forty-four patients with chronic stroke were randomly allocated to one of the configurations and used the system for 35 minutes a day for 5 days a week during 4 weeks. RESULTS: Our results revealed significant within-subject improvements at most of the standard clinical evaluation scales for all groups. Specifically we observe that the beneficial effects of VR-based training are modulated by the use/nonuse of compensatory movement strategies and the specific sensorimotor contingencies presented to the user, that is, visual feedback versus combined visual haptic feedback. CONCLUSIONS: Our findings suggest that the beneficial effects of VR-based neurorehabilitation systems such as the Rehabilitation Gaming System for the treatment of chronic stroke depend on the specific interface systems used. These results have strong implications for the design of future VR rehabilitation strategies that aim at maximizing functional outcomes and their retention. Clinical Trial Registration- This trial was not registered because it is a small clinical study that evaluates the feasibility of prototype devices.

Drive competition underlies effective allostatic orchestration.

Living systems ensure their fitness by self-regulating. The optimal matching of their behavior to the opportunities and demands of the ever-changing natural environment is crucial for satisfying physiological and cognitive needs. Although homeostasis has explained how organisms maintain their internal states within a desirable range, the problem of orchestrating different homeostatic systems has not been fully explained yet. In the present paper, we argue that attractor dynamics emerge from the competitive relation of internal drives, resulting in the effective regulation of adaptive behaviors. To test this hypothesis, we develop a biologically-grounded attractor model of allostatic orchestration that is embedded into a synthetic agent. Results show that the resultant neural mass model allows the agent to reproduce the navigational patterns of a rodent in an open field. Moreover, when exploring the robustness of our model in a dynamically changing environment, the synthetic agent pursues the stability of the self, being its internal states dependent on environmental opportunities to satisfy its needs. Finally, we elaborate on the benefits of resetting the model's dynamics after drive-completion behaviors. Altogether, our studies suggest that the neural mass allostatic model adequately reproduces self-regulatory dynamics while overcoming the limitations of previous models.

From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans.

Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in the regulation of this activity is thought to give rise to normal variation in human traits, and disruptions are thought to potentially underlie a spectrum of neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs' Syndrome, intellectual disability). Hypotheses related to E/I dysfunction have the potential to provide cross-diagnostic explanations and to combine genetic and neurological evidence that exists within and between psychiatric conditions. However, the hypothesis has been difficult to test because: (1) it lacks specificity-an E/I dysfunction could pertain to any level in the neural system- neurotransmitters, single neurons/receptors, local networks of neurons, or global brain balance - most researchers do not define the level at which they are examining E/I function; (2) We lack validated methods for assessing E/I function at any of these neural levels in humans. As a result, it has not been possible to reliably or robustly test the E/I hypothesis of psychiatric disorders in a large cohort or longitudinal patient studies. Currently available, in vivo markers of E/I in humans either carry significant risks (e.g., deep brain electrode recordings or using Positron Emission Tomography (PET) with radioactive tracers) and/or are highly restrictive (e.g., limited spatial extent for Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Spectroscopy (MRS). More recently, a range of novel Electroencephalography (EEG) features has been described, which could serve as proxy markers for E/I at a given level of inference. Thus, in this perspective review, we survey the theories and experimental evidence underlying 6 novel EEG markers and their biological underpinnings at a specific neural level. These cheap-to-record and scalable proxy markers may offer clinical utility for identifying subgroups within and between diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. However, we argue that studies in clinical populations are premature. To maximize the potential of prospective EEG markers, we first need to understand the link between underlying E/I mechanisms and measurement techniques.