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Decoding Depth of Meditation: EEG Insights from Expert Vipassana Practitioners

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Decoding Depth of Meditation: Electroencephalography Insights From Expert Vipassana Practitioners

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Reggente, N., Kothe, C., Brandmeyer, T., Hanada, G., Simonian, N., Mullen, S., & Mullen, T. (2024). Decoding Depth of Meditation: EEG Insights from Expert Vipassana Practitioners. Biological Psychiatry Global Open Science, 5(1), 100402. https://doi.org/10.1016/j.bpsgos.2024.100402

Reggente, Nicco, et al. “Decoding Depth of Meditation: EEG Insights from Expert Vipassana Practitioners.” Biological Psychiatry Global Open Science, vol. 5, no. 1, Oct. 2024, p. 100402, doi:10.1016/j.bpsgos.2024.100402.

@article{Reggente_Kothe_Brandmeyer_Hanada_Simonian_Mullen_Mullen_2024, title={Decoding Depth of Meditation: EEG Insights from Expert Vipassana Practitioners}, volume={5}, url={https://doi.org/10.1016/j.bpsgos.2024.100402}, DOI={10.1016/j.bpsgos.2024.100402}, number={1}, journal={Biological Psychiatry Global Open Science}, author={Reggente, Nicco and Kothe, Christian and Brandmeyer, Tracy and Hanada, Grant and Simonian, Ninette and Mullen, Sean and Mullen, Tim}, year={2024}, month=oct, pages={100402} }

Since it’s inception, the Institute for Advanced Consciousness Studies has been driven by a mission to create what we call a “Qualia Compass”—a tool that can collect “mental souvenirs” from hard-to-achieve states of consciousness. The purpose? To help individuals return to those states more easily and remain there longer through personalized, multivariate neurofeedback. This ambitious project seeks to, first, democratize access to profound meditative experiences that typically require years of dedicated practice.

Our recent research represents a significant step toward this goal, successfully decoding self-reported meditative depth using EEG data from expert Vipassana practitioners. Rather than simply distinguishing meditation from mind-wandering (as most previous research has done), we’ve tackled the more nuanced challenge of differentiating between various depths of meditation—a critical advancement for developing effective neurofeedback tools.

Beyond Binary Classifications

Traditional approaches to meditation research often suffer from what we might call the “soup versus salad problem.” The vast majority of neuroscientific investigations into meditation have focused on comparing meditation to mind-wandering—essentially contrasting two fundamentally different cognitive states, akin to comparing soup to salad. While this approach has yielded valuable insights, it falls short of our more ambitious goal: understanding the subtle gradations within meditative states themselves.

Our research adopts the perspective of a master chef who, rather than comparing soup to salad, focuses on discerning subtle variations within a single complex soup (variations A1 and A2). This approach acknowledges that to truly master the art of making exceptional soup—or in our case, to understand and facilitate profound meditation—we must develop a nuanced understanding of the elements that differentiate various iterations of the same fundamental state. By examining gradations within the meditative experience, we can identify the specific neural patterns that characterize progressively deeper states of meditation.

This focus on nuances within a singular state promises to deepen our understanding of meditation’s neural correlates. Yet pursuing this approach introduces a methodological challenge that French philosopher Auguste Comte identified: one cannot simultaneously observe oneself walking on the street from a balcony. In meditation research, this manifests as the “observer effect”—the act of reporting one’s meditative state inevitably disrupts that state. That is, the moment we try and observe the state we wish to measure is the same moment that it is no longer that state.

The Spontaneous Emergence Solution

To address this dilemma, we introduced “spontaneous emergence” as an experiential sampling method. Rather than interrupting meditation with systematic probes, participants naturally reported their meditative depth when they spontaneously emerged from deeper states. This approach yielded comparable decoding performance to traditional probing methods while preserving ecological validity—providing a less intrusive way to gather phenomenological data during meditation.

Our study involved 34 expert Vipassana practitioners who visited our lab on two separate occasions. Using source-localized EEG activity in the theta, alpha, and gamma frequency bands, we built machine learning models that could predict meditative depth in unseen sessions—essentially, we trained the models on data from one visit and tested them on the other.

Remarkable Results

Despite conventional EEG channel-level methods failing to show significant correlations with meditation depth, our multivariate machine learning approaches demonstrated remarkable accuracy in predicting participants’ self-reported depth ratings. This suggests that the neural dynamics of varying meditation depths are too complex and non-linear to be captured by traditional univariate analyses.

Our best models achieved performance levels comparable to those seen in established EEG-based brain-computer interfaces, with area under the curve (AUC) scores approaching 0.81 for distinguishing between low and high meditation depths. To put this in perspective, this means our algorithm could correctly classify 81 out of 100 different depth reportings in the high versus low domain. This level of accuracy is particularly impressive considering the subtle, internally-generated nature of meditative states, approaching the performance of well-established brain-computer interfaces used for detecting much more distinct phenomena like imagined hand movements.

For the continuous 0-5 scale, our models achieved a mean absolute error (MAE) as low as 1.15, substantially better than chance (1.51). Think of this as a meditation depth “thermometer” that’s typically just over one degree off—if a practitioner reports being at level 4, our algorithm might predict 3 or 5, but rarely would it mistake a shallow level 1 for a profound level 5 experience.

Perhaps most remarkably, the “spontaneous emergence” method—where participants naturally reported their depth when emerging from meditation—performed just as well as the more intrusive probing approach, while providing more ecological validity and yielding more data points.

The connectivity patterns we observed revealed fascinating neural signatures across frequency bands. In the theta band, we found increased frontal-midline activity—a known signature of focused-attention meditation—within a complex interplay of activations in right parietal and frontal pole regions. Alpha band activity showed distinct increases in midline parietal regions complemented by left parietal reduction, partially mapping onto trait-level mindfulness. Meanwhile, gamma band activity revealed increased occipitoparietal activity causally influencing midline parietal regions.

Ecological Validity and Phenomenological Coherence

Further analysis revealed that the spontaneous emergence method not only generated significantly more data points (45.6% higher reporting frequency) than the probe-based approach but also demonstrated stronger correlations with post-session assessments of meditation quality. Participants reported substantially higher confidence in their depth ratings when self-determining when to report (“emerge” condition) versus when prompted (“probe” condition). This enhanced metacognitive certainty was reflected in post-session questionnaire responses, where Toronto Mindfulness Scale (TMS) scores and Meditation Depth Index (MEDI) ratings showed stronger alignment with data collected during spontaneous emergence blocks. The phenomenological coherence between in-session spontaneous reports and post-session reflective assessments suggests that the emergence method captures more authentic aspects of the meditative experience—preserving the integrity of both the subjective experience and its neural correlates. This finding has profound implications for meditation research methodology, indicating that less intrusive approaches may yield more ecologically valid data while simultaneously improving participants’ ability to maintain deeper meditative states.

Next Steps: Personalized Neurofeedback

These findings represent a critical step toward developing more sophisticated, multivariate-based neurofeedback systems. By identifying the neural correlates representing different gradations of meditative depth, we can move beyond the limitations of traditional univariate neurofeedback protocols that risk misinterpreting certain states of consciousness as meditative.

Our ultimate goal is to use these personalized, real-time neural signatures to create adaptive neurofeedback systems that guide individuals toward deeper meditation states—serving as the “training wheels” that gradually become unnecessary as practitioners develop their own metacognitive skills for recognizing and maintaining profound meditative states.

By achieving a better understanding of Vipassana meditation, which underlies many modern mindfulness practices, this research stands to significantly advance the rapidly expanding realm of meditation-based interventions, potentially making these powerful practices more accessible and effective for a broader population.

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an illustration of neuroprint showing a brain being dipped in ink as an imagery for personalized responses to different pieces of neural content.

In Pursuit of a ‘Neuroprint’ for Neuroscience-Based Personalization

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The Challenge of Individual Variation

Just as fingerprints represent multivariate patterns with sufficient uniqueness and stability to serve as forensic evidence in criminal proceedings, our brains harbor distinctive topographies of response to the world around us. These neural landscapes, shaped by genetics, experience, and countless moments of conscious and unconscious processing, hold the key to understanding why we respond so differently to therapeutic interventions, experiential technologies, and even the media we consume.

Consider how a single piece of music might bring one person to tears (or chills) while leaving another unmoved, or how a particular therapeutic approach might transform one individual’s life while proving ineffective for another. These variations are not mere quirks of personality but reflect fundamental differences in our neural architecture – differences that have remained largely opaque to systematic investigation and, even more so, utility.

The Precedent for Precision

In an age where Netflix algorithms predict our entertainment preferences and genetic analyses forecast our responses to pharmaceuticals, we stand at the threshold of a new frontier in precision neuroscience. The modern digital landscape has already demonstrated the power of predictive analytics in domains ranging from social media engagement to consumer behavior. Companies like Strain Genie have pioneered the use of genetic markers to predict individual responses to various compounds. Yet the brain, our most complex organ, has remained somewhat elusive to such precise prognostic approaches.

Foundations in Cognitive Neuroscience Research

Our research team’s work in utilizing resting-state fMRI to predict therapeutic outcomes in OCD patients represents a crucial step forward. By analyzing neural activity patterns before treatment, we’ve successfully forecast therapeutic responses six weeks into the future. Similarly, our ability to predict aesthetic chills from trait questionnaires has opened new windows into understanding transformative experiences and their potential impact on mental health.

Of particular clinical significance is our work in stratifying disorders of consciousness, where predictive neuroimaging has proven instrumental in determining care trajectories and probability of recovery for individuals in comatose states. These prognostic capabilities hold profound implications for medical decision-making and resource allocation in critical care settings. Additionally, our research has extended into the domain of gender-affirming healthcare, where we’ve successfully predicted individual responses to cross-sex hormone therapy, enabling more personalized and effective treatment protocols.

Further expanding the scope of predictive neuroscience, our investigations into memory encoding strength have yielded remarkable insights with direct applications to forensic psychology. By quantifying the neural correlates of memory formation, we can now predict the reliability of episodic recall – a breakthrough that holds particular relevance for evaluating the veracity of eyewitness testimonies in legal proceedings. This development represents a significant advance in bringing objective neuroscientific measures to bear on crucial questions of judicial reliability.

The Neuroprint Protocol: A Theoretical Framework

Building upon these foundational studies, we propose Neuroprint – a theoretical protocol conceived at the Institute for Advanced Consciousness Studies (IACS) that transcends traditional psychometric approaches by capturing the intricate dimensionality of individual neural response patterns. This framework acknowledges the brain as a uniquely sophisticated information processing system whose response characteristics extend far beyond the reductive categorizations offered by personality inventories or standard resting-state analyses.

The protocol’s methodological innovation lies in its systematic mapping of neural response topographies across multiple domains of conscious experience. Drawing inspiration from the precise characterization achieved in fingerprint analysis, where minute variations in dermal ridge patterns yield unique identifiers, Neuroprint employs a multi-layered stimulus paradigm designed to probe both fundamental sensory processing and higher-order cognitive responses.

At its foundation, the protocol implements precisely calibrated sensory sweeps that systematically traverse fundamental perceptual dimensions. Visual stimulation progresses through the complete visible spectrum (380-700 nm), executing bidirectional ROYGBIV sequences that map chromatic response characteristics with high granularity. Parallel auditory stimulation spans the full range of human hearing (20 Hz to 20 kHz), methodically exploring both pure tonal progressions and complex harmonic structures that reveal individual variations in acoustic processing.

Building upon this foundational sensory mapping, the protocol extends into increasingly complex domains of perceptual and cognitive processing. A carefully curated sequence of ecologically valid stimuli probes universal response patterns: the sound of infant vocalizations that tap into deeply conserved caregiving circuits, the rhythmic patterns of biological motion that engage social perception networks, and the acoustic signatures of environmental threats that activate ancient survival mechanisms. These universal probes – ranging from heartbeats and breathing patterns to footsteps and tool use sounds – provide a baseline for understanding fundamental neural response characteristics.

a high sensory stimuli neuroprint

The protocol culminates in its most sophisticated element: the systematic presentation of cultural motifs that engage higher-order cognitive and emotional processing networks. This component employs rapid sequences of culturally embedded stimuli – fragments of wedding marches and funeral dirges, snippets of victory celebrations and lullabies, elements of ritual music and social ceremonies – each carefully selected to probe the neural signatures of learned cultural associations while maintaining cross-cultural validity. Urban soundscapes (traffic patterns, subway rhythms, cafe ambiance) and natural phenomena (flowing water, crackling fire, rustling leaves) provide additional layers of ecological complexity.

Each stimulus presentation within this hierarchical paradigm elicits distinct spatiotemporal patterns of neural activation, characterized by unique amplitudes, latencies, and topographical distributions across recording channels. These evoked responses, analogous to individual ridges in a fingerprint, constitute discrete features in a high-dimensional space of neural reactivity. The aggregation of these responses – thousands of precisely characterized neural events spanning sensory, cognitive, and cultural domains – generates a comprehensive feature set that forms the individual’s neuroprint. This multidimensional characterization of neural response patterns provides an unprecedented framework for capturing the brain’s inherent complexity, establishing a quantitative basis for understanding individual differences in experiential processing.

The proposed protocol would orchestrate a carefully choreographed sequence of stimuli: sweeping colors that dance across the visual field, precisely calibrated sounds that traverse the frequency spectrum, and tactile sensations that map the body’s landscape. Like collecting thousands of evoked response potentials, each stimulus interaction would contribute to a high-dimensional portrait of neural function. These responses, captured through EEG or fMRI, would form the features of an individual’s unique neuroprint – a theoretical construct that we anticipate will bridge current limitations in predictive neuroscience.

Predictive Power Through Pattern Recognition

The true power of this approach lies in its predictive capabilities. By leveraging advanced machine learning techniques and collaborative filtering – similar to how Netflix identifies patterns among viewers – we can use your neuroprint in concert with our growing database of behavioral responses to interventions to minimize uncertainty about your potential response to various interventions. This approach transcends traditional one-size-fits-all paradigms, offering a pathway to truly personalized therapeutic and experiential interventions.

Future Directions and Planned Implementation

The theoretical implications of the Neuroprint protocol extend far beyond academic interest. Planned collaborations with Lumena and the Institute for Meditation Brainwave Research will explore practical applications that could revolutionize how we approach mental health treatment, meditation practice, and experiential therapy. By understanding the unique neural fingerprint that each individual brings to these interventions, we anticipate being able to better match people with the approaches most likely to benefit them.

As IACS prepares to implement and validate this theoretical framework, our vision extends beyond mere data collection – we aim to map the infinite variations of human experience, one neuroprint at a time. This endeavor represents a step toward a future where interventions can be precisely tailored to each individual’s neural architecture, maximizing effectiveness while minimizing the cost – both temporal and financial – of finding the right approach for each person.

The pursuit of realizing the Neuroprint protocol represents more than just technological innovation; it embodies our commitment to understanding the profound uniqueness of each human brain. In this pursuit, we’re not just proposing a tool – we’re developing a new language for understanding the individual variations that make each of us uniquely human, and in doing so, laying the groundwork for new pathways to healing and transformation.

Arousal Regulation by the External Globus Pallidus: A New Node for the Mesocircuit Hypothesis

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Arousal Regulation by the External Globus Pallidus: A New Node for the Mesocircuit Hypothesis

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Zheng, Z. S., Reggente, N., & Monti, M. M. (2023). Arousal regulation by the external globus pallidus: a new node for the mesocircuit hypothesis. Brain Sciences, 13(1), 146. https://doi.org/10.3390/brainsci13010146

Zheng, Zhong Sheng, et al. “Arousal regulation by the external globus pallidus: a new node for the mesocircuit hypothesis.” Brain Sciences, vol. 13, no. 1, Jan. 2023, p. 146, doi:10.3390/brainsci13010146.

@article{Zheng_Reggente_Monti_2023, title={Arousal regulation by the external globus pallidus: a new node for the mesocircuit hypothesis}, volume={13}, url={https://doi.org/10.3390/brainsci13010146}, DOI={10.3390/brainsci13010146}, number={1}, journal={Brain Sciences}, author={Zheng, Zhong Sheng and Reggente, Nicco and Monti, Martin M.}, year={2023}, month=jan, pages={146} }

Introduction

In the intricate architecture of the brain, the External Globus Pallidus (GPe) has traditionally been recognized as a cornerstone in motor control. However, recent research reveals a more profound narrative—one where the GPe emerges not just as a facilitator of movement, but as a pivotal regulator of arousal and consciousness. This evolving perspective invites us to reconsider the Mesocircuit Hypothesis, integrating the GPe as a crucial node that orchestrates the delicate interplay between wakefulness and sleep.

The Mesocircuit Hypothesis and the GPe’s Expanding Role

The Mesocircuit Hypothesis (MH) offers a framework for understanding consciousness, focusing primarily on the thalamus as the central relay in sustaining arousal. Yet, the basal ganglia, particularly the GPe, have often been overlooked in this context. The GPe, once seen merely as a relay in motor pathways, now emerges as an integral regulator within the mesocircuit, influencing both motor and non-motor functions.

  • Enhancing the MH Framework: Integrating the GPe into the MH enriches our understanding of arousal regulation, bridging the gap between motor control and cognitive states.
  • Interconnected Networks: The GPe’s extensive connections with cortical and subcortical structures underscore its role in harmonizing neural processes essential for maintaining consciousness.
  • Dynamic Modulation: The GPe’s ability to modulate inhibitory and excitatory signals positions it as a dynamic regulator, vital for adaptive arousal responses.

GPe’s Role in Sleep-Wake Regulation

The GPe’s influence extends deeply into the regulation of sleep-wake cycles, orchestrating the transitions that govern our daily rhythms. Animal studies illuminate the GPe’s dual capacity to promote wakefulness and facilitate restful sleep, underscoring its significance in maintaining sleep architecture.

  • Damage to the GPe: Disruption of the GPe leads to heightened wakefulness intertwined with fragmented sleep patterns, revealing its role in stabilizing sleep.
  • Stimulation of the GPe: Enhancing GPe activity promotes sleep, particularly non-REM (NREM) sleep, crucial for restorative processes.
  • Connection with the Thalamic Reticular Nucleus (TRN): The GPe’s interaction with the TRN plays a vital role in sensory gating, ensuring that extraneous stimuli do not disrupt sleep by modulating thalamocortical neuron activity.

Neurochemical Insights: Adenosine and Dopamine

The GPe’s interactions with neurochemicals such as adenosine and dopamine reveal the biochemical underpinnings of arousal regulation.

  • Adenosine (A2A) Receptors: Abundant in the striatum, these receptors facilitate sleep promotion when activated. The GPe’s interaction with adenosine receptors positions it as a mediator in the transition to sleep.
  • Dopamine (D2) Receptors: Dopamine modulates GPe activity through D2 receptors, influencing arousal states. In conditions like Parkinson’s Disease, where dopamine levels are compromised, sleep disturbances often manifest, highlighting the GPe’s role in maintaining sleep-wake balance.

The GPe in Disorders of Consciousness

Beyond its role in normal sleep-wake regulation, the GPe emerges as a key player in disorders of consciousness (DOC), offering new avenues for understanding and treatment.

  • Functional Connectivity and Atrophy: In DOC patients, pallidal atrophy, particularly within the GPe, correlates with measures of behavioral arousal and neural complexity, suggesting its vital role in sustaining consciousness.
  • Pharmacological Interventions: Medications like Zolpidem (Ambien), typically used for insomnia, paradoxically enhance arousal in some DOC patients. This effect is likely mediated by the GPe’s extensive GABAergic connections, which modulate thalamocortical activity.
  • Differential Connectivity: The GPe’s robust connections with the prefrontal cortex (PFC) and central thalamic nuclei, as opposed to the GPi’s motor-centric connections, indicate a specialized role in cognitive arousal and consciousness.

Integrative Perspectives on the GPe’s Functionality

The GPe’s complex role in the broader neural landscape extends beyond traditional motor control, embedding itself within the nuanced interplay of consciousness and arousal.

  • Bridging Motor and Cognitive Domains: The GPe’s involvement in both motor and non-motor functions positions it as a crucial intersection within the brain’s network, influencing cognitive processes as well as physical actions.
  • Therapeutic Potential: Understanding the GPe opens new avenues for therapeutic interventions, particularly in treating sleep disorders, DOC, and neuropsychiatric conditions through targeted modulation of its activity.
Figure 1
Proposed Striato-Pallidal Circuitries for Promoting Sleep. Two potential routes by which the GPe may mediate cortical activity are illustrated: (A) the Cortico-Striato-Pallido-Cortical route and (B) the Cortico-Striato-Pallido-Reticulo-Thalamo-Cortical route. These circuits highlight the GPe’s role in regulating sleep-wake cycles through its connections with the cortex and thalamic reticular nucleus.

Conclusion

The External Globus Pallidus, once a peripheral player in the orchestra of neural functions, now takes center stage as a conductor of arousal and consciousness. Its integration into the Mesocircuit Hypothesis not only broadens our understanding of the brain’s regulatory mechanisms but also offers new insights into the treatment of disorders related to consciousness and sleep. As we continue to explore the GPe’s intricate pathways and interactions, we open the door to innovative therapies and a deeper understanding of the brain’s orchestration of wakefulness and rest.

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VR for Cognition and Memory

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Manuscript, Proceedings, Protocol-002

This blog post is based on a recent book chapter “VR for Cognition and Memory” in Current Topics in Behavioral Neuroscience: Virtual Reality in Behavioral Neuroscience: New Insights and Methods. This work presents a review of research on VR’s ability to provide ecologically valid environments to study memory and cognition and discusses how features like interactivity, locomotion, and contextual control engage the brain’s memory systems more naturally than lab studies.

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VR for Cognition and Memory

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Reggente N. (2023). VR for Cognition and Memory. Current topics in behavioral neurosciences, 10.1007/7854_2023_425. Advance online publication. https://doi.org/10.1007/7854_2023_425

Reggente N. VR for Cognition and Memory [published online ahead of print, 2023 Jul 14]. Curr Top Behav Neurosci. 2023;10.1007/7854_2023_425. doi:10.1007/7854_2023_425

Reggente, Nicco. “VR for Cognition and Memory.” Current topics in behavioral neurosciences, 10.1007/7854_2023_425. 14 Jul. 2023, doi:10.1007/7854_2023_425

Revolutionizing Cognition Research with Virtual Reality

For decades, scientists have worked tirelessly to elucidate the intricate neural machinery supporting human cognition. This endeavor is certainly not for the faint of heart, as formidable challenges present themselves at every turn.

“To study cognition holistically means investigating interconnections between its rich repertoire of functions, including attention, reasoning, language, and memory. Memory is a particularly crucial facet, as it supports and subserves all other aspects of cognition; no cognitive task can be accomplished without memory.”

A holistic understanding demands that we study cognition as it operates in its natural habitat – the real world. Otherwise, as the parable of the blind men and the elephant warns, we risk gross mischaracterizations. Researchers must therefore conduct experiments in “verisimilar contexts (i.e. contexts appearing as the RW)” to achieve ecological validity.

Virtual reality (VR) presents an unprecedented opportunity in this regard. By simulating the real world, we can now study memory and cognition with enhanced veridicality.

“The environmental customization afforded by VR makes it an ideal tool for studying cognition in an ecologically valid fashion. Through the lens of memory studies, this chapter showcases the ways in which VR has advanced a meaningful and applicable understanding of cognition.”

The article presents a thorough review of research that showcases how VR is revolutionizing the study of cognition and memory.

Bridging the Gap Between Lab and Real-World Cognition

Traditional lab experiments often possess limited generalizability, whereas VR can provide naturalistic environments and tasks that echo real-world demands, easily bolstering ecological validity. Previous work has made a compelling case for how VR enhances the ecological validity of fMRI memory research.

VR experiences engage recollection-based memory retrieval akin to real events, unlike lab stimuli which rely more on familiarity. Indeed, VR experiences appear to be retrieved via recollection-based processes similar to those that support autobiographical/recollection memory, whereas retrieval of conventional screen experiences seems more similar to familiarity. This makes VR apt for integrated cognition and memory research.

VR Permits for Information to be Situation in Space

Most importantly, VR permits realistic navigation around virtual environments (c.f.), affording users with a sense of space (the scaffolding of memory). Both philosophers and psychologists alike postulate that brains have evolved solely to support purposeful and predictable movement. Many posit that the ontogeny of episodic memory relates to the onset of locomotion during infancy that scales with Hippocampal development (which also provides a mechanism for infantile amnesia and age-related episodic memory loss). One source of evidence to support this proposition is in the life cycle of the bluebell tunicate. This filter feeder begins to digest a substantial chunk of its cerebral ganglion once identifying a suitable undersea perch to spend the rest of its existence. This phenomenon suggests that once it has served its purpose as a neural network supporting movement, the cerebral ganglion yields greater utility to the organism as nutrition.

From chemotaxis to cognitive maps, a representation of space is necessary for meaningful movement. A neural instantiation of a map that provides spatial bookmarks of an organism’s experiences, demarcating the locations of nutrition and enemies within an environment, is a fundamental component of brains. Indeed, there is a primacy of spatial content in the neural representation of events. Spatial information is often recalled earliest in the retrieval process, and the degree to which individuals report confidence in their autobiographical memories is predicted by their knowledge of the spatial layout of the setting in which the memory occurred. The Method of Loci (a.k.a. Memory Palace) mnemonic has long been appreciated for its ability to increase memory by imagining to-be-remembered information placed at familiar locations. Past work used a VR implantation of this technique to suggest that the principal component behind mnemonic efficacy is the explicit binding of the objects to a spatial location and revealed a tight relationship between spatial memory (SM) and free recall of encoded objects. These observations showcase that space and memory are inextricably linked at conceptual and neuronal levels – a notion that has become entrenched in popular culture; the phrase “out of space” is often used when indicating a computer’s memory is full.

a fantastical virtual environment that could be used to study the relationship between objects, positions, and memory.

If space is the inescapable wallpaper that serves as the backdrop for all experience, then it follows that as our spatial or environmental context changes, so should the neural activity underlying diverse cognitive processes. Given that VR can easily change environments, it provides an unparalleled landscape with which to study the intersection of space, memory, and cognition.

Additionally, VR enables human analogs of spatial memory research previously limited to animal models, like virtual radial arm mazes. This facilitates powerful translational research from rodents to humans.

Key Features of VR That Facilitate Cognition Research

Below are some features highlighted by the chapter that are exclusive to VR. Such features permit real-world scenarios with increased experimental control and significantly less costs.

  • VR provides absolute control over the environment. This permits isolation and systematic manipulation of spatial contexts, immersion, emotions, embodiment, etc.
  • Rapid teleportation between environments induces robust context-dependent learning, a fundamental principle in memory encoding.
  • Interactivity and locomotion increase embodiment and navigational involvement, enhancing hippocampal memory systems.
  • Implicit metrics like gaze, paths, and object interactions generate objective measures of memory and attention unbiased by subjective reporting.
  • Brain imaging during VR reveals in vivo neural correlates of cognition impossible with real-world navigation.
  • VR spatial mnemonics such as the Method of Loci can provide performance improvements over just imagination by standardizing and controlling the environments.

Applications of VR for Assessing and Enhancing Cognition

Conventional measures of memory typically focus on core content (i.e., the “what”) instead of the true binding that happens in actual episodes (i.e., “what,” where,” and “when”). They also often use verbal materials, which makes the test sensitive to performance in non-memory domains, permitting for compensatory strategies which could erroneously reveal normal “memory.” Subjective reports rarely scale with performance on traditional memory tests, warranting criticism that such measures wrongly estimate memory capacities for everyday situations. For example, patients reporting topographical memory deficits have preserved ability in tabletop tests of spatial or geographical knowledge. Additionally, cognitive complaints in amnesiacs typically show little correlation with verbal memory tests used in clinical settings.

VR tasks, however, have been more reliable in tracking self and caregiver reports of deficits that impact quality of life. The points below highlight other aspects of VR that can increase the ecological validity of both the detection and amelioration of memory deficits.

  • VR scenarios like virtual stores and routes enable sensitive, ecologically valid tools to identify mild cognitive impairment early.
  • VR spatial navigation paradigms can differentiate Alzheimer’s from milder impairment based on hippocampal recruitment patterns.
  • VR enables safe exposure therapy for memory deficits induced by trauma and realistic training for brain injury rehabilitation.
  • Spatial mnemonic techniques adapted to VR boost memory beyond baseline abilities in healthy individuals.
  • VR puzzles engage aging minds, increasing motivation. Long-term regimes may prevent decline. As one study found, “6 months of VR training powerfully increased long-term recall.”
  • VR training could augment real-world cognition and rehabilitate deficits, with proven memory transfer effects.

In conclusion, VR enables an unprecedented ability to understand real-world cognition, precisely diagnose impairments, and develop interventions that enhance memory and cognition. The immersive, interactive nature of VR environments engages our brains’ memory systems far more naturally than traditional lab studies.

The inherently engaging qualities of VR, coupled with its ability to implicitly quantify and enhance memory, make it a powerful tool in populations spanning from pediatrics to the elderly.

Indeed, VR may catalyze discoveries about the very mechanisms underlying human consciousness itself, which intimately relies on episodic memory. By augmenting these processes, VR could profoundly transform our experience and understanding of consciousness. The future of cognition research has never looked more exciting.

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Current State of Potential Mechanisms Supporting Low-Intensity Focused Ultrasound for Neuromodulation

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Published in Frontiers in Human Neuroscience in 2022, this review intended to answer how ultrasound for neuromodulation works

Our review titled, Current state of potential mechanisms supporting low intensity focused ultrasound for neuromodulation, attempts to address the following questions: 1) How can we alter the amount of mechanical energy or other properties of the mechanical energy using the sonication parameters available with each device, 2) How are neuronal tissue affected by mechanical energy, and 3) How do those sonication parameters change the type of neuromodulation (i.e., excitatory or suppressive)? We reviewed the theoretical mechanisms of action for neuromodulation and the empirical findings tracking all the sonication parameters used to elucidate the possible link between the proposed mechanisms of action and the choice of sonication parameters. This is still an emerging field, but a tabulation of the empirical findings and theoretical models is needed to help clinicians and researchers choose the best paradigm to use.

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DellItalia, John, et al. “Current state of potential mechanisms supporting low intensity focused ultrasound for neuromodulation.” Frontiers in Human Neuroscience: 228.

DellItalia, J., Sanguinetti, J. L., Monti, M. M., Bystritsky, A., & Reggente, N. Current state of potential mechanisms supporting low intensity focused ultrasound for neuromodulation. Frontiers in Human Neuroscience, 228.

DellItalia, John, Joseph L. Sanguinetti, Martin M. Monti, Alexander Bystritsky, and Nicco Reggente. “Current state of potential mechanisms supporting low intensity focused ultrasound for neuromodulation.” Frontiers in Human Neuroscience: 228

DellItalia, J., Sanguinetti, J.L., Monti, M.M., Bystritsky, A. and Reggente, N., Current state of potential mechanisms supporting low intensity focused ultrasound for neuromodulation. Frontiers in Human Neuroscience, p.228.

DellItalia J, Sanguinetti JL, Monti MM, Bystritsky A, Reggente N. Current state of potential mechanisms supporting low intensity focused ultrasound for neuromodulation. Frontiers in Human Neuroscience.:228.

Science Without Jargon

Science should be accessible to everyone. However, dense jargon-filled articles can make it difficult for non-experts to engage with research. Making science accessible promotes scientific literacy and informed decision-making. In this post, we summarize our recent article for a lay audience.

 

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How ultrasound for neuromodulation works

Non-invasive brain stimulation has been used to modulate the activity of neural tissue without the need for surgical procedures to implant devices or permanently alter the neural tissue. Non-invasive brain stimulation has been used for neuromodulation across empirical research and clinical practices using transcranial electrical stimulation and transcranial magnetic stimulation. These types of neural modulation use electric (i.e., transcranial electrical stimulation) or magnetic (i.e., transcranial magnetic stimulation) fields applied outside the skull to induce changes in the electrochemical activity underneath the device within and around neurons. These fields tend to affect larger areas and affect all the neural tissue that the fields pass through. Thus, this limits which brain regions can be targeted precisely or individually.

An alternative to the putative non-invasive brain stimulation is devices using ultrasound. Ultrasound has been used for decades by clinicians to image various parts of the body, but recently ultrasound devices have begun to be used for neuromodulation. Ultrasound doesn’t use electric or magnetic fields, rather it generates acoustic waves that are a mechanical force. This mechanical force can be focused on a precise area with only the maximal mechanical energy converging on millimeter-sized region. This allows for deeper and/or smaller brain regions to be targeted compared to transcranial electrical stimulation and transcranial magnetic stimulation. However, the different energy source compared to electric or magnetic fields requires a different understanding of how neuromodulation occurs. Without this understanding, effective uses of ultrasound in empirical research and clinical practices will be limited.

Ultrasound’s acoustic waves have the characteristic properties of wavelength, amplitude, and frequency. Wavelength is the distance between two peaks within the wave, the amplitude is the height of the wave, and frequency is the number of peaks in a second. Each of these properties affects the total amount of mechanical energy delivered by the ultrasound device and other sonication parameters. The total energy can be measured by either the average amount in a spatial region or the average amount delivered over time typically converted into the units of watts per centimeter squared. In addition to the intensity, the total energy delivered over time is affected by the duty cycle, which is the percentage of time the sonication occurs. The duty cycle also determines if a paradigm is pulsed or continuous. Pulsed paradigms are any duty cycle below 100 percent, which allows for breaks between the sonication, compared to a continuous application of ultrasound. The frequency of the ultrasound’s acoustic waves is related to the sonication parameters of center frequency and pulse repetition frequency. The center frequency is set by the device manufacturer, which is the frequency delivered by the device and this frequency is related to the spatial precision of the acoustic wave delivered. The pulse repetition frequency is the frequency of the acoustic wave delivered by the pulsed paradigm. The final commonly adjusted sonication parameter is sonication duration (i.e., total time of acoustic wave delivered).

The mechanical energy delivered by the ultrasound device has seven proposed mechanisms to affect the activity of groups of neurons. Neurons are connected and each neuron’s activity either helps to excite other neurons connected to it or suppresses the activity of the neurons connected to it. These signals involve both electrical and chemical signaling. Since ultrasound is mechanical, the mechanisms of action proposed describes: 1) effects of mechanical energy on the temperature., 2) how the neurons detect and transform that mechanical energy to electrical or chemical signaling (i.e., mechanosensitive ion channels), or 3) how mechanical energy interacts with the elasticity of neurons to change the electrical properties or structure of neurons (e.g., direct flexoelectricity, change of membrane conformational states, or sonoporation).

Ultrasound has been used for decades to destroy malignant tissue by using enough intensity to generate larger changes in temperature. These large changes in temperature are not seen in the intensity ranges used in non-invasive brain stimulation. Despite the lower intensity used, there is still a mechanical force acting on the neurons. Some neurons have specific mechanisms for detecting external mechanical forces. These are most well understood in our tactile sensations. When our hand presses against a surface, specialized neurons detect the mechanical force by getting stretched which allows for chemical and electrical signaling to occur. The amount and distribution of neurons with similar properties in the brain is an active area of research. In addition to these specialized neurons, the mechanical energy from ultrasound can change the electrical properties of neurons by distorting the shape. The specific configuration of the membrane allows for electrical signals (i.e., direct flexoelectricity) to be produced as the mechanical energy changes the alignment of the interior and exterior parts of the membrane. On top of these alignment changes, there are pressure changes which can also generate both chemical and electrical changes from the changes in membrane conformational states.

Additionally, the neuron’s membranes can have changes to their permeability called sonoporation allowing for electrical changes that can elicit the neuron to fire. This process was investigated how the ultrasound’s pulse repetition frequency, intensity, or duty cycle could produce excitatory or suppressive effects. The key sonication parameter that best predicted differences in neuronal activity was duty cycle. Higher duty cycles between 10% to 70%, typically excited neurons, while lower duty below 10% created suppressive effects. Unfortunately, this one parameter did not predict the suppressive findings well, but the excitatory findings were almost all exclusively found between 10% to 70% duty cycle.

While duty cycle was predictive of some results found in the literature, it left most of the results unexplained. More models and theories are needed to expand the understanding of the mechanisms of action. Hopefully, this review gives a basic knowledge base to clinicians and researchers to use in their treatments or experiments. As the understanding of the mechanisms of action expand, more nuanced treatments and experiments can be used.

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Figures & Captions

Feel free to use these figures in your articles, blogs, and presentations. If you do, please cite this work.

Figure 1.

Low intensity focused ultrasound general principles. (A) A depiction of a typical LIFU experimental setup. A participant is seated (2) with an US device (5) firmly pressed against their head held in place by an arm (3). The US device is controlled by a computer system (4) and targeted using infrared system (1). (B) Depiction of the mechanical wave properties (amplitude, wavelength, and frequency) used in US stimulation. (C) Spatial intensities of the mechanical wave. (D) Temporal intensities of the mechanical wave. (E) Two exemplary pulsation schemes: pulsed (in yellow) and continuous (in teal). Both the pulsing schemes have a customizable sonication duration with inter stimulation interval with the DC parameter (i.e., the ratio of tone burst duration over pulse repetition period) determining the pulsing scheme.

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Figure 2.

Proposed ultrasonic stimulation’s mechanisms for neuromodulation. Depicted in column 1 are six neuronal membranes (four with an ion channel [rows A,C,D,E] and two neuronal membranes [rows B,F] with polar lipid bilayer) and a neuron with the microtubules highlighted (row G). Depicted in column 2, these membranes have four types of electrophysiological-mechanical coupling during an action potential: change in membrane conformation state, thermodynamic waves, direct flexoelectricity, and opening of mechanosensitive ion channels (see Section above). Column 3 depicts these same four electrophysiological-mechanical coupling during US stimulation along with three other possible mechanisms of US’s neuromodulation: thermal modulation, sonoporation and cavitation, and microtubule resonance (see Section above).

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Figure 3.

Neuronal intramembrane cavitation excitation model. Plaksin et al. (2014, 2016) proposed the NICE model hypothesizing sonoporation (see Figure 2F) as US’s mechanism of neuromodulation. The US’s DC (see Figure 1E) determines the polarity of neuromodulation. A low DC (i.e., below 5%) during a stimulation’s off-periods will preferentially activate thalamic reticular neurons (TRN), thalamocortical neurons (TCN), and low-threshold spiking (LTS) interneurons via T-type voltage-gated calcium channels (see Section above for full description) producing an inhibitory effect. A high DC (i.e., over 20%) during the on-periods will preferentially activate regular spiking (RS) pyramidal cells and fast spiking (FS) interneurons while suppressing the LTS interneurons producing an overall excitatory effect. This excitatory effect is simulated using a basic network model of LTS, FS, and RS neurons connected with excitatory and inhibitory synapses and thalamic inputs. The network model predicts an optimum excitation of 70% DC.

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Figure 4.

Excitatory and suppressive empirical findings’ relationships to DC, PRF, ISPPA, fc, and SD. DC, PRF, ISPPA, fc, and SD are used as grouping factors for excitatory and suppressive findings. We used density plots for each study, but studies with multiple sonication parameters have each one plotted. In the top panel, high DC, above 10%, has the vast majority of the excitatory findings. While ow DC, less than 10%, contains the majority of the suppressive findings, there are still approximately 30% of the suppressive findings above 10% DC. The top panel is highlighted in red because DC is the one sonication parameter that has any distinction between excitatory and suppressive findings. In the four bottom panels, PRF, ISPPA, fc, and SD has no clear distinction between excitatory and suppressive findings.

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