In vivo ephaptic coupling allows memory network formation

Mixed selectivity: Cellular computations for complexity

The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity. If their activity can be expressed as a weighted sum, then they exhibit linear mixed selectivity; otherwise, they exhibit nonlinear mixed selectivity. Neural representations based on diverse nonlinear mixed selectivity are high dimensional; hence, they confer enormous flexibility to a simple downstream readout neural circuit. However, a simple neural circuit cannot possibly encode all possible mixtures of variables simultaneously, as this would require a combinatorially large number of mixed selectivity neurons. Gating mechanisms like oscillations and neuromodulation can solve this problem by dynamically selecting which variables are mixed and transmitted to the readout.

Extensive soma-soma plate-like contact sites (ephapses) connect suprachiasmatic nucleus neurons

The hypothalamic suprachiasmatic nucleus (SCN) is the central pacemaker for mammalian circadian rhythms. As such, this ensemble of cell-autonomous neuronal oscillators with divergent periods must maintain coordinated oscillations. To investigate ultrastructural features enabling such synchronization, 805 coronal ultrathin sections of mouse SCN tissue were imaged with electron microscopy and aligned into a volumetric stack, from which selected neurons within the SCN core were reconstructed in silico. We found that clustered SCN core neurons were physically connected to each other via multiple large soma-to-soma plate-like contacts. In some cases, a sliver of a glial process was interleaved. These contacts were large, covering on average ∼21% of apposing neuronal somata. It is possible that contacts may be the electrophysiological substrate for synchronization between SCN neurons. Such plate-like contacts may explain why the synchronization of SCN neurons is maintained even when chemical synaptic transmission or electrical synaptic transmission via gap junctions is blocked. Such ephaptic contact-mediated synchronization among nearby neurons may therefore contribute to the wave-like oscillations of circadian core clock genes and calcium signals observed in the SCN.

Transcranial electric stimulation modulates firing rate at clinically relevant intensities

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.

Laying the foundations for a theory of consciousness: the significance of critical brain dynamics for the formation of conscious states

Empirical evidence indicates that conscious states, distinguished by the presence of phenomenal qualities, are closely linked to synchronized neural activity patterns whose dynamical characteristics can be attributed to self-organized criticality and phase transitions. These findings imply that insight into the mechanism by which the brain controls phase transitions will provide a deeper understanding of the fundamental mechanism by which the brain manages to transcend the threshold of consciousness. This article aims to show that the initiation of phase transitions and the formation of synchronized activity patterns is due to the coupling of the brain to the zero-point field (ZPF), which plays a central role in quantum electrodynamics (QED). The ZPF stands for the presence of ubiquitous vacuum fluctuations of the electromagnetic field, represented by a spectrum of normal modes. With reference to QED-based model calculations, the details of the coupling mechanism are revealed, suggesting that critical brain dynamics is governed by the resonant interaction of the ZPF with the most abundant neurotransmitter glutamate. The pyramidal neurons in the cortical microcolumns turn out to be ideally suited to control this interaction. A direct consequence of resonant glutamate-ZPF coupling is the amplification of specific ZPF modes, which leads us to conclude that the ZPF is the key to the understanding of consciousness and that the distinctive feature of neurophysiological processes associated with conscious experience consists in modulating the ZPF. Postulating that the ZPF is an inherently sentient field and assuming that the spectrum of phenomenal qualities is represented by the normal modes of the ZPF, the significance of resonant glutamate-ZPF interaction for the formation of conscious states becomes apparent in that the amplification of specific ZPF modes is inextricably linked with the excitation of specific phenomenal qualities. This theory of consciousness, according to which phenomenal states arise through resonant amplification of zero-point modes, is given the acronym TRAZE. An experimental setup is specified that can be used to test a corollary of the theory, namely, the prediction that normally occurring conscious perceptions are absent under experimental conditions in which resonant glutamate-ZPF coupling is disrupted.

Neural Geometrodynamics, Complexity, and Plasticity: A Psychedelics Perspective

We explore the intersection of neural dynamics and the effects of psychedelics in light of distinct timescales in a framework integrating concepts from dynamics, complexity, and plasticity. We call this framework neural geometrodynamics for its parallels with general relativity's description of the interplay of spacetime and matter. The geometry of trajectories within the dynamical landscape of "fast time" dynamics are shaped by the structure of a differential equation and its connectivity parameters, which themselves evolve over "slow time" driven by state-dependent and state-independent plasticity mechanisms. Finally, the adjustment of plasticity processes (metaplasticity) takes place in an "ultraslow" time scale. Psychedelics flatten the neural landscape, leading to heightened entropy and complexity of neural dynamics, as observed in neuroimaging and modeling studies linking increases in complexity with a disruption of functional integration. We highlight the relationship between criticality, the complexity of fast neural dynamics, and synaptic plasticity. Pathological, rigid, or "canalized" neural dynamics result in an ultrastable confined repertoire, allowing slower plastic changes to consolidate them further. However, under the influence of psychedelics, the destabilizing emergence of complex dynamics leads to a more fluid and adaptable neural state in a process that is amplified by the plasticity-enhancing effects of psychedelics. This shift manifests as an acute systemic increase of disorder and a possibly longer-lasting increase in complexity affecting both short-term dynamics and long-term plastic processes. Our framework offers a holistic perspective on the acute effects of these substances and their potential long-term impacts on neural structure and function.

Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain

Spatiotemporal patterns of cellular resting potential regulate several aspects of development. One key aspect of the bioelectric code is that transcriptional and morphogenetic states are determined not by local, single-cell, voltage levels but by specific distributions of voltage across cell sheets. We constructed and analyzed a minimal dynamical model of collective gene expression in cells based on inputs of multicellular voltage patterns. Causal integration analysis revealed a higher-order mechanism by which information about the voltage pattern was spatiotemporally integrated into gene activity, as well as a division of labor among and between the bioelectric and genetic components. We tested and confirmed predictions of this model in a system in which bioelectric control of morphogenesis regulates gene expression and organogenesis: the embryonic brain of the frog Xenopus laevis. This study demonstrates that machine learning and computational integration approaches can advance our understanding of the information-processing underlying morphogenetic decision-making, with a potential for other applications in developmental biology and regenerative medicine.

Biophysical control of plasticity and patterning in regeneration and cancer

Cells and tissues display a remarkable range of plasticity and tissue-patterning activities that are emergent of complex signaling dynamics within their microenvironments. These properties, which when operating normally guide embryogenesis and regeneration, become highly disordered in diseases such as cancer. While morphogens and other molecular factors help determine the shapes of tissues and their patterned cellular organization, the parallel contributions of biophysical control mechanisms must be considered to accurately predict and model important processes such as growth, maturation, injury, repair, and senescence. We now know that mechanical, optical, electric, and electromagnetic signals are integral to cellular plasticity and tissue patterning. Because biophysical modalities underly interactions between cells and their extracellular matrices, including cell cycle, metabolism, migration, and differentiation, their applications as tuning dials for regenerative and anti-cancer therapies are being rapidly exploited. Despite this, the importance of cellular communication through biophysical signaling remains disproportionately underrepresented in the literature. Here, we provide a review of biophysical signaling modalities and known mechanisms that initiate, modulate, or inhibit plasticity and tissue patterning in models of regeneration and cancer. We also discuss current approaches in biomedical engineering that harness biophysical control mechanisms to model, characterize, diagnose, and treat disease states.

Transcranial electric stimulation modulates firing rate at clinically relevant intensities

Notwithstanding advances with low-intensity transcranial electrical stimulation (TES), there remain questions about the efficacy of clinically realistic electric fields on neuronal function. We used Neuropixels 2.0 probe with 384 channels in an in-vivo rat model of TES 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). We demonstrate that electric fields below 0.5 V/m acutely modulate firing rate in 5% of neurons recorded in the hippocampus. At these intensities, average firing rate effects increased monotonically with electric field intensity at a rate of 7 % per V/m. For the majority of excitatory neurons, firing increased for cathodal stimulation and diminished for anodal stimulation. While more diverse, the response of inhibitory neurons followed a similar pattern on average, likely as a result of excitatory drive. Our results indicate that responses to TES at clinically relevant intensities are driven by a fraction of high-responder excitatory neurons, with polarity-specific effects. We conclude that transcranial electric stimulation is an effective neuromodulator at clinically realistic intensities.