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A) Time points of significant GC field interactions from FEF to SEF for all cued locations. Time is shown on the vertical axis and cued locations on the horizontal. Significant interactions are shown in yellow. B) Similar to (A). Significant GC field interactions for the reverse direction, from SEF to FEF. C) GC strengths (vertical axis) of FEF to SEF (left panel) and SEF to FEF (right panel) field interactions across time (horizontal axis) for (θ = 120 • . D) Correlations (left panel) and P-values (right panel) between FEF principal axes and temporal windows during which GC field interactions from FEF to SEF were significant. Principal axes are shown on the vertical axis (from first to fourth as we move downwards) and cued locations on the horizontal axis. E) Similar to (D) for SEF principal axes.
Source publication
It is increasingly clear that memories are distributed across multiple brain areas. Such "engram complexes" are important features of memory formation and consolidation. Here, we test the hypothesis that engram complexes are formed in part by bioelectric fields that sculpt and guide the neural activity and tie together the areas that participate in...
Citations
... Recently this coupling was highlighted in article [97] in modeling of nonlocal representation of memories: "It is increasingly clear that memories are distributed across multiple brain areas. Such "engram complexes" are important features of memory formation and consolidation. ...
The past few years have seen a surge in the application of quantum-like (QL) modeling in fields such as cognition, psychology, and decision-making. Despite the success of this approach in explaining various psychological phenomena, there remains a potential dissatisfaction due to its lack of clear connection to neurophysiological processes in the brain. Currently, it remains a phenomenological approach. In this paper, we develop a QL representation of networks of communicating neurons. This representation is not based on standard quantum theory but on generalized probability theory (GPT), with a focus on the operational measurement framework (see section 2.1 for comparison of classical, quantum, and generalized probability theories). Specifically, we use a version of GPT that relies on ordered linear state spaces rather than the traditional complex Hilbert spaces. A network of communicating neurons is modeled as a weighted directed graph, which is encoded by its weight matrix. The state space of these weight matrices is embedded within the GPT framework, incorporating effect-observables and state updates within the theory of measurement instruments-a critical aspect of this model. Under the specific assumption regarding 1 neuronal connectivity, the compound system S = (S 1 , S 2) of neuronal networks is represented using the tensor product. This S 1 ⊗ S 2 representation significantly enhances the computational power of S. The GPT-based approach successfully replicates key QL effects, such as order, non-repeatability, and disjunction effects-phenomena often associated with decision interference. Additionally, this framework enables QL modeling in medical diagnostics for neurological conditions like depression and epilepsy. While the focus of this paper is primarily on cognition and neuronal networks, the proposed formalism and methodology can be directly applied to a broad range of biological and social networks. Furthermore, it supports the claims of superiority made by quantum-inspired computing and can serve as the foundation for developing QL-based AI systems, specifically utilizing the QL representation of oscillator networks.
... Many living systems display electrochemical patterns that are homologous to those of neurons, including the electromagnetic fields that have been hypothesized to be important for consciousness [77][78][79][80][81][82][83]. Most bodily cells regulate membrane-bound ion channels to maintain a polarized electrical state; however, neurons display notably hyperpolarized resting potentials (-70 mV). ...
It is commonly assumed that a useful theory of consciousness (ToC) will, among other things, explain why consciousness is associated with brains. However, the findings of evolutionary biology, developmental bioelectricity, and synthetic bioengineering are revealing the ancient pre-neural roots of many mechanisms and algorithms occurring in brains – the implication of which is that minds may have preceded brains. Most of the work in the emerging field of diverse intelligence emphasizes externally observable problem-solving competencies in unconventional media, such as cells, tissues, and life-technology chimeras. Here, we inquire about the implications of these developments for theories that make a claim about what is necessary and/or sufficient for consciousness. Specifically, we analyze popular current ToCs to ask: what features of the theory specifically pick out brains as a privileged substrate of inner perspective, or, do the features emphasized by the theory occur elsewhere. We find that the operations and functional principles described or predicted by most ToCs are remarkably similar, that these similarities are obscured by reference to particular neural substrates, and that the focus on brains is more driven by convention and limitations of imagination than by any specific content of existing ToCs. Encouragingly, several contemporary theorists have made explicit efforts to apply their theories to synthetic systems in light of the recent wave of technological developments in artificial intelligence (AI) and organoid bioengineering. We suggest that the science of consciousness should be significantly open to minds in unconventional embodiments.
... Action potentials propagating along axon bundles could cause synchronization and timing fluctuations of spikes (Ramón and Moore, 1978;Douglas and Blair, 2024), aiding in the integration of subtle odor signals in olfactory neurons (Bokil et al., 2001) and potentially synchronizing distant brain regions (Schmidt et al., 2021). Ephaptic coupling has been proposed to play a role in linking distributed memory networks by forming neural networks (engram complexes) for memory (Pinotsis and Miller, 2023). ...
... The hypothesis of information integration through ephaptic coupling suggests that electric fields could rapidly integrate spatially distributed information, contributing to memory representation and consciousness (Pinotsis and Miller, 2023;Vogeley and Fink, 2003;McFadden, 2020). However, this process remains poorly understood as it involves integrating information within a finite time. ...
The evolution of brain-expressed genes is notably slower than that of genes expressed in other tissues, a phenomenon likely due to high-level functional constraints. One such constraint might be the integration of information by neuron assemblies, enhancing environmental adaptability. This study explores the physiological mechanisms of information integration in neurons through three types of synchronization: chemical, electromagnetic, and quantum. Chemical synchronization involves the diffuse release of neurotransmitters like dopamine and acetylcholine, causing transmission delays of several milliseconds. Electromagnetic synchronization encompasses action potentials, electrical gap junctions, and ephaptic coupling. Electrical gap junctions enable rapid synchronization within cortical GABAergic networks, while ephaptic coupling allows structures like axon bundles to synchronize through extracellular electromagnetic fields, surpassing the speed of chemical processes. Quantum synchronization is hypothesized to involve ion coherence during ion channel passage and the entanglement of photons within the myelin sheath. Unlike the finite-time synchronization seen in chemical and electromagnetic processes, quantum entanglement provides instantaneous non-local coherence states. Neurons might have evolved from slower chemical diffusion to rapid temporal synchronization, with ion passage through gap junctions within cortical GABAergic networks potentially facilitating both fast gamma band synchronization and quantum coherence. This mini-review compiles literature on these three synchronization types, offering new insights into the physiological mechanisms that address the binding problem in neuron assemblies.
... Computational models, in which properties and effects of neurally generated e-fields are simulated, offer additional support for ephaptic coupling. In one study, biophysical simulation of neuronal ensembles predicted LFP signals recorded during a spatial task better when the extracellular fields were modeled to weakly feed back into local neuron clusters (although not for all task conditions; [50]). In another study, neural activity was found to propagate along an unfolded slice of hippocampus even when synaptic and gap junction transmission were blocked; simulations tailored to the data suggest that these effects emerge with biologically plausible field strengths [51]. ...
... In the study, coworker presented a compelling argument suggesting that memory formation in the brain is associated with ephaptic processes that intrinsically shape and control neuronal activity by establishing connections between the brain areas [24]. Their study provided empirical evidence for ephaptic coupling between two cortical regions in vivo. ...
... The heightened complexity indicates enhanced organization and more frequent transitions between diverse integrative states within brain networks, as evidenced by Billings (2018) [50]. This prompts the hypothesis that ephaptic coupling in vivo might play a pivotal role in memory formation and consolidation, as demonstrated by Pinotsis (2023) [24,75]. ...
... The heightened complexity indicates enhanced organization and more frequent transitions between diverse integrative states within brain networks, as evidenced by Billings (2018) [50]. This prompts the hypothesis that ephaptic coupling in vivo might play a pivotal role in memory formation and consolidation, as demonstrated by Pinotsis (2023) [24,75]. ...
The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of the brain and nuanced levels of cognitive integration. Recent advances in neuroscience have brought the mechanisms underlying the generation of highly intricate dynamics, emergent patterns, and sophisticated oscillatory signals into question. Within this context, our study, in alignment with current research, postulates the hypothesis that ephaptic communication, in addition to synaptic mediation’s, may emerge as a prime candidate for unraveling optimal brain complexity. Ephaptic communication, hitherto little studied, refers to direct interactions of the electric field between adjacent neurons, without the mediation of traditional synapses (electrical or chemical). We propose that these electric field couplings may provide an additional layer of connectivity that facilitates the formation of complex patterns and emergent dynamics in the brain. In this investigation, we conducted a comparative analysis between two types of networks utilizing the Quadratic Integrate-and-Fire Ephaptic model (QIF-E): (I) a small-world synaptic network (ephaptic-off) and (II) a mixed composite network comprising a small-world synaptic network with the addition of an ephaptic network (ephaptic-on). Utilizing the Multiscale Entropy methodology, we conducted an in-depth analysis of the responses generated by both network configurations, with complexity assessed by integrating across all temporal scales. Our findings demonstrate that ephaptic coupling enhances complexity under specific topological conditions, considering variables such as time, spatial scales, and synaptic intensity. These results offer fresh insights into the dynamics of communication within the nervous system and underscore the fundamental role of ephapticity in regulating complex brain functions.
... These can take on a host of forms, such as sources or sinks, which expand or contract around a point, spirals which rotate around a point, and saddles which are usually the superposition of different interacting waves. These patterns have been consistently observed in mesoscopic and macroscopic neural recordings [30,[35][36][37][38][39], and are thought to play crucial roles in cortical computation [40,41], modulating excitation-inhibition balance [42], memory [43,44], and perception [45][46][47]. ...
5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) is a psychedelic drug known for its uniquely profound effects on subjective experience, reliably eradicating the perception of time, space, and the self. However, little is known about how this drug alters large-scale brain activity. We collected naturalistic electroencephalography (EEG) data of 29 healthy individuals before and after inhaling a high dose (12mg) of vaporised synthetic 5-MeO-DMT. We replicate work from rodents showing amplified low-frequency oscillations, but extend these findings with novel tools for characterising the organisation and dynamics of complex low-frequency spatiotemporal fields of neural activity. We find that 5-MeO-DMT radically reorganises low-frequency flows of neural activity, causing them to become incoherent, heterogeneous, viscous, fleeting, nonrecurring, and to cease their typical travelling forwards and backwards across the cortex compared to resting state. Further, we find a consequence of this reorganisation in broadband activity, which exhibits slower, more stable, low-dimensional behaviour, with increased energy barriers to rapid global shifts. These findings provide the first detailed empirical account of how 5-MeO-DMT sculpts human brain dynamics, revealing a novel set of cortical slow wave behaviours, with significant implications for extant neuroscientific models of serotonergic psychedelics.
... Ephaptic communication, known as communication through electric fields, may originate from a single neuron or a group of neurons 8,10,11,16 . Ephaptic neuronal communication, characterized by electrical field interactions between adjacent nerve cells, underscores an interconnection beyond traditional synapses and enhances our understanding of brain communication in the formation of memory and consciousness 9,17,18 . The impact of ephaptic communication on neurophysiological brain functions is a subject of rigorous investigation. ...
The brain is understood as an intricate biological system composed of numerous elements. It is susceptible to various physical and chemical influences, including temperature. The literature extensively explores the conditions that influence synapses in the context of cellular communication. However, the understanding of how the brain’s global physical conditions can modulate ephaptic communication remains limited due to the poorly understood nature of ephapticity. This study proposes an adaptation of the Hodgkin and Huxley (HH) model to investigate the effects of ephaptic entrainment in response to thermal changes (HH-E). The analysis focuses on two distinct neuronal regimes: subthreshold and suprathreshold. In the subthreshold regime, circular statistics are used to demonstrate the dependence of phase differences with temperature. In the suprathreshold regime, the Inter-Spike Interval are employed to estimate phase preferences and changes in the spiking pattern. Temperature influences the model’s ephaptic interactions and can modify its preferences for spiking frequency, with the direction of this change depending on specific model conditions and the temperature range under consideration. Furthermore, temperature enhance the anti-phase differences relationship between spikes and the external ephaptic signal. In the suprathreshold regime, ephaptic entrainment is also influenced by temperature, especially at low frequencies. This study reveals the susceptibility of ephaptic entrainment to temperature variations in both subthreshold and suprathreshold regimes and discusses the importance of ephaptic communication in the contexts where temperature may plays a significant role in neural physiology, such as inflammatory processes, fever, and epileptic seizures.
... Furthermore, ephaptic coupling has been identified as a crucial 63 factor in governing synchronization and spike timing in neurons [22][23][24]. 64 In the study, coworker presented a compelling argument suggesting that memory 65 formation in the brain is associated with ephaptic processes that intrinsically shape and 66 control neuronal activity by establishing connections between the brain areas [25]. Their 67 study provided empirical evidence for ephaptic coupling between two cortical regions in 68 vivo. ...
The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of the brain and nuanced levels of cognitive integration. Recent advances in neuroscience have brought the mechanisms underlying the generation of highly intricate dynamics, emergent patterns, and sophisticated oscillatory signals into question. Within this context, our study, in alignment with current research, posits the hypothesis that ephaptic communication may emerge as the primary candidate for unraveling optimal brain complexity. In this investigation, we conducted a comparative analysis between two types of networks utilizing the Quadratic Integrate-and-Fire Ephaptic model (QIF-E): (I) a small-world synaptic network (ephaptic-off) and (II) a mixed composite network comprising a small-world synaptic network with the addition of an ephaptic network (ephaptic-on). Utilizing the Multiscale Entropy methodology, we conducted an in-depth analysis of the responses generated by both network configurations, with complexity assessed by integrating across all temporal scales. Our findings demonstrate that ephaptic coupling enhances complexity under specific topological conditions, considering variables such as time, spatial scales, and synaptic intensity. These results offer fresh insights into the dynamics of communication within the nervous system and underscore the fundamental role of ephapticity in regulating complex brain functions.
... Electric fields generated during theta rhythms in the hippocampus of rats [75] can be in the range of 1-2 V/m and up to 2 V/m during slow waves in the visual cortex of ferrets [5]. New evidence that such weak fields can have an effect on neuronal function comes from in vitro experiments [5][6][7][8] as well as computational modeling [76][77][78]. These studies mostly demonstrated a modulation of the timing of rhythmic neural activity, and relied on highly coherent rhythms that are not commonly observed in vivo. ...
Background
Notwithstanding advances with low-intensity transcranial electrical stimulation (tES), there remain questions about the efficacy of clinically realistic electric fields on neuronal function.
Objective
To measure electric fields magnitude and their effects on neuronal firing rate of hippocampal neurons in freely moving rats, and to establish calibrated computational models of current flow.
Methods
Current flow models were calibrated on electric field measures in the motor cortex (n = 2 anesthetized rats) and hippocampus. A Neuropixels 2.0 probe with 384 channels was used in an in-vivo rat model of tES (n = 4 freely moving and 2 urethane anesthetized rats) to detect effects of weak fields on neuronal firing rate. High-density field mapping and computational models verified field intensity (1 V/m in hippocampus per 50 μA of applied skull currents).
Results
Electric fields of as low as 0.35 V/m (0.25–0.47) acutely modulated average firing rate in the hippocampus. At these intensities, firing rate effects increased monotonically with electric field intensity at a rate of 11.5 % per V/m (7.2–18.3). For the majority of excitatory neurons, firing increased for soma-depolarizing stimulation and diminished for soma-hyperpolarizing stimulation. While more diverse, the response of inhibitory neurons followed a similar pattern on average, likely as a result of excitatory drive.
Conclusion
In awake animals, electric fields modulate spiking rate above levels previously observed in vitro. Firing rate effects are likely mediated by somatic polarization of pyramidal neurons. We recommend that all future rodent experiments directly measure electric fields to insure rigor and reproducibility.
... Communication via electric fields is called ephaptic communication 8,10,11,16 , and may have its origin in a single neuron or in a group of neurons 8 . ephaptic communication, characterized by electrical interactions between adjacent nerve cells, highlights an interconnection beyond conventional synapses, expanding the understanding of brain communication for the formation of memory and consciousness 9,17,18 . The role of ephaptic communication on neurophysiological functions that occur in the brain is a topic of intense research. ...
... The role of ephaptic communication on neurophysiological functions that occur in the brain is a topic of intense research. However, hypotheses about the influence of ephaptic communication have been raised, such as that ephaptic communication is not only classified as an epiphenomenon, that is, a side effect caused by neuronal activity, but rather as a causal communication that can influence the neuronal dynamics 9,10,[15][16][17] . Studies show that, although the stimulus caused by this external electric field is insufficient to generate action potentials, however, the ephaptic fields can modulated and influence the synchronization of action potentials 10,11,19,20 . ...
The brain is understood as an intricate biological system composed of multiple elements. It is susceptible to diverse physical and chemical influences, including temperature. The literature widely explores the conditions that affect synapses in the context of cellular communications. However, the understanding of how brain global physical conditions can modulate ephaptic communication remains limited, because the still poorly understood nature of ephapticity. This study proposes an adaptation of the Hodgkin and Huxley model, HH-E, to investigate the effects of ephaptic entrainment in response to thermal changes. The analysis focus on two distinct neuronal regimes: subthreshold and suprathreshold. In the subthreshold regime, the circular statistic is used to show the phase differences dependence on temperature. In the suprathreshold regime, the Population Vector and the Inter-Spike Interval are used to estimate phase preferences and changes in the spiking pattern. Temperature affects positively the HH-E model spiking frequency. At high temperatures the HH-E model collapses and no more spiking are observed. Moreover, temperature difference improves the anti-phase between spikes and the ephaptic external signal. In the suprathreshold regime, the ephaptic entrainment is influenced by temperature, specially at low frequencies. Finally, this study reveals the susceptibility of ephaptic entrainment to temperature variations in both subthreshold and suprathreshold regimes and discusses the importance of ephaptic communication in pathological contexts in which temperature play an important role in neural physiology, such as inflammatory processes, fever and epileptic seizures.
