Network resonance can be generated independently at distinct levels of neuronal organization

Entrainment by transcranial alternating current stimulation: Insights from models of cortical oscillations and dynamical systems theory

Signature of neuronal oscillations can be found in nearly every brain function. However, abnormal oscillatory activity is linked with several brain disorders. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that can potentially modulate neuronal oscillations and influence behavior both in health and disease. Yet, a complete understanding of how interacting networks of neurons are affected by tACS remains elusive. Entrainment effects by which tACS synchronizes neuronal oscillations is one of the main hypothesized mechanisms, as evidenced in animals and humans. Computational models of cortical oscillations may shed light on the entrainment effects of tACS, but current modeling studies lack specific guidelines to inform experimental investigations. This study addresses the existing gap in understanding the mechanisms of tACS effects on rhythmogenesis within the brain by providing a comprehensive overview of both theoretical and experimental perspectives. We explore the intricate interactions between oscillators and periodic stimulation through the lens of dynamical systems theory. Subsequently, we present a synthesis of experimental findings that demonstrate the effects of tACS on both individual neurons and collective oscillatory patterns in animal models and humans. Our review extends to computational investigations that elucidate the interplay between tACS and neuronal dynamics across diverse cortical network models. To illustrate these concepts, we conclude with a simple oscillatory neuron model, showcasing how fundamental theories of oscillatory behavior derived from dynamical systems, such as phase response of neurons to external perturbation, can account for the entrainment effects observed with tACS. Studies reviewed here render the necessity of integrated experimental and computational approaches for effective neuromodulation by tACS in health and disease.

Interleaved single and bursting spiking resonance in neurons

Under in vivo conditions, CA1 pyramidal cells from the hippocampus display transitions from single spikes to bursts. It is believed that subthreshold hyperpolarization and depolarization, also known as down and up-states, play a pivotal role in these transitions. Nevertheless, a central impediment to correlating suprathreshold (spiking) and subthreshold activity has been the technical difficulties of this type of recordings, even with widely used calcium imaging or multielectrode recordings. Recent work using voltage imaging with genetically encoded voltage indicators has been able to correlate spiking patterns with subthreshold activity in a variety of CA1 neurons, and recent computational models have been able to capture these transitions. In this work, we used a computational model of a CA1 pyramidal cell to investigate the role of intrinsic conductances and oscillatory patterns in generating down and up-states and their modulation in the transition from single spiking to bursting. Specifically, the emergence of distinct spiking resonances between these two spiking modes that share the same voltage traces in the presence of theta or gamma oscillatory inputs, a phenomenon we call interleaved single and bursting spiking resonance. We noticed that these resonances do not necessarily overlap in frequency or amplitude, underscoring their relevance for providing flexibility to neural processing. We studied the conductance values of three current types that are thought to be critical for the bursting behavior: persistent sodium current (INaP) and its conductance GNaP, delayed rectifier potassium (IKDR) and its conductance GKDR, and hyperpolarization-activated current (Ih) and its conductance Gh. We conclude that the intricate interplay of ionic currents significantly influences the neuronal firing patterns, transitioning from single to burst firing during sustained depolarization. Specifically, the intermediate levels of GNaP and GKDR facilitate spiking resonance at gamma frequency inputs. The resonance characteristics vary between single and burst firing modes, each displaying distinct amplitudes and resonant frequencies. Furthermore, low GNaP and high GKDR values lock bursting to theta frequencies, while high GNaP and low GKDR values lock single spiking to gamma frequencies. Lastly, the duration of quiet intervals plays a crucial role in determining the likelihood of transitioning to either bursting or single spiking modes. We confirmed that the same features were present in previously recorded in vivo voltage-imaging data. Understanding these dynamics provides valuable insights into the fundamental mechanisms underlying neuronal excitability under in vivo conditions.

Sleep links hippocampal propensity for epileptiform activity to its viscerosensory inputs

The development of a seizure relies on two factors. One is the existence of an overexcitable neuronal network and the other is a trigger that switches normal activity of that network into a paroxysmal state. While mechanisms of local overexcitation have been the focus of many studies, the process of triggering remains poorly understood. We suggest that, apart from the known exteroceptive sources of reflex epilepsy such as visual, auditory or olfactory signals, there is a range of interoceptive triggers, which are relevant for seizure development in Temporal Lobe Epilepsy (TLE). The hypothesis proposed here aims to explain the prevalence of epileptic activity in sleep and in drowsiness states and to provide a detailed mechanism of seizures triggered by interoceptive signals.

CHOLINERGIC MODULATION OF CELLULAR RESONANCE IN NON-HUMAN PRIMATE HIPPOCAMPUS

Acetylcholine modulates the network physiology of the hippocampus, a crucial brain structure that supports cognition and memory formation in mammals 1-3. In this and adjacent regions, synchronized neuronal activity within theta-band oscillations (4-10Hz) is correlated with attentive processing that leads to successful memory encoding 4-10. Acetylcholine facilitates the hippocampus entering a theta oscillatory regime and modulates the temporal organization of activity within theta oscillations 11,12. Unlike rodents that exhibit constant theta oscillations during movement and exploration, primates only manifest theta oscillations in transient bouts during periods of acute attention-despite conserved hippocampal anatomy 13-16. The phasic nature of primate theta oscillations and their susceptibility to muscarinic antagonists 17, suggest that acetylcholine afferents acutely modulate local circuitry, resulting in a temporary shift in hippocampal rhythmic dynamics. However, we lack a mechanistic understanding that links cellular physiology to emergent theta-rhythmic network dynamics. We explored the hypothesis that acetylcholine induces a distinct modulation of cellular properties to facilitate synchronization within the theta band in non-human primate neurons. Here we show that non-human primate neurons from the CA1 region of monkey hippocampus are not homogeneous in their voltage response to inputs of varying frequencies, a phenomenon known as cellular resonance 18,19. We classified these neurons as 'resonant' or 'non-resonant'. Under the influence of carbachol, these two classes of neurons become indistinguishable in their resonance, suggesting that acetylcholine transiently creates a homogeneous susceptibility to inputs within the theta range. This change is mediated by metabotropic acetylcholine receptors that enhance sag potentials, indicating that acetylcholine acts on principal neurons to modulate Hyperpolarization-activated Cyclic Nucleotide-gated channels. Our results reveal a mechanism through which acetylcholine can rapidly modulate intrinsic properties of primate hippocampal neurons to facilitate synchronization within theta-rhythmic circuits, providing insight into the unique features of primate hippocampal physiology.

Coherent Changes in Neural Motor Network Activity during Levodopa-Induced Dyskinesia in a Rat Model of Parkinson's Disease

BACKGROUND

Long-term use of levodopa, a metabolic precursor of dopamine (DA) for alleviation of motor symptoms in Parkinson's disease (PD), can cause a serious side effect known as levodopa-induced dyskinesia (LID). With the development of LID, high-frequency gamma oscillations (~100 Hz) are registered in the motor cortex (MCx) in patients with PD and rats with experimental PD. Studying alterations in the activity within major components of motor networks during transition from levodopa-off state to dyskinesia can provide useful information about their contribution to the development of abnormal gamma oscillations and LID.

METHODS

Freely moving rats with unilateral 6-hydroxydopamine hydrobromide (6-OHDA)-induced nigral DA cell lesions were administered a high dose of levodopa for 7 days. Local field potentials (LFPs) and neuronal activity were recorded from electrodes implanted in the motor cortex (MCx), ventromedial nucleus of the thalamus (VM), and substantia nigra pars reticulata nucleus (SNpr).

RESULTS

Levodopa reduced the power of beta oscillations (30-36 Hz) associated with bradykinesia in PD rats in three divisions of the motor neural network (MCx, VM, and SNpr) and prompted subsequent emergence of robust high-frequency gamma oscillations (80-120 Hz) in VM and MCx, but not SNpr, LFPs. Gamma oscillations were strongly associated with the occurrence of abnormal involuntary movements (AIMs) and accompanied by an increase in spiking rates in the VM and MCx and enlarged spike-LFP synchronization with cortical gamma oscillations (68% in the VM and 34% in the MCx). In contrast, SNpr LFPs did not exhibit gamma oscillations during LID, and neuronal activity in most recordings (87%) was largely decreased and not synchronized with VM or MCx LFPs. Administration of the antidyskinetic drug 8-hydroxy-2-(dipropylamino)-tetraline hydrobromide (8-OH-DPAT) restored the initial characteristics of LFPs (30-36 Hz oscillations), rates of neuronal activity, and bradykinesia. Inhibition of VM neurons by the gamma-aminobutyric acid (GABA-A)-agonist muscimol during LID eliminated high gamma oscillations in the MCx and VM, but not dyskinesia, suggesting that gamma oscillations are not critical for the expression of AIMs. In contrast, chemogenetic activation of SNpr neurons during LID eliminated both gamma oscillations and dyskinesia.

CONCLUSIONS

These findings suggest that levodopa treatment leads to crucial reduction of inhibitory control over motor networks due to a large decline in spiking of most SNpr GABAergic projecting neurons, which causes persistent hyperactivity in motor circuits, leading to the appearance of thalamocortical gamma oscillations and LID.

Local activation of CA1 pyramidal cells induces theta-phase precession

Hippocampal theta-phase precession is involved in spatiotemporal coding and in generating multineural spike sequences, but how precession originates remains unresolved. To determine whether precession can be generated directly in hippocampal area CA1 and disambiguate multiple competing mechanisms, we used closed-loop optogenetics to impose artificial place fields in pyramidal cells of mice running on a linear track. More than one-third of the CA1 artificial fields exhibited synthetic precession that persisted for a full theta cycle. By contrast, artificial fields in the parietal cortex did not exhibit synthetic precession. These findings are incompatible with precession models based on inheritance, dual-input, spreading activation, inhibition-excitation summation, or somato-dendritic competition. Thus, a precession generator resides locally within CA1.

Propagation of Oscillations in the Indirect Pathway of the Basal Ganglia

Oscillatory signals propagate in the basal ganglia from prototypic neurons in the external globus pallidus (GPe) to their target neurons in the substantia nigra pars reticulata (SNr), internal pallidal segment, and subthalamic nucleus. Neurons in the GPe fire spontaneously, so oscillatory input signals can be encoded as changes in timing of action potentials within an ongoing spike train. When GPe neurons were driven by an oscillatory current in male and female mice, these spike-timing changes produced spike-oscillation coherence over a range of frequencies extending at least to 100 Hz. Using the known kinetics of the GPe→SNr synapse, we calculated the postsynaptic currents that would be generated in SNr neurons from the recorded GPe spike trains. The ongoing synaptic barrage from spontaneous firing, frequency-dependent short-term depression, and stochastic fluctuations at the synapse embed the input oscillation into a noisy sequence of synaptic currents in the SNr. The oscillatory component of the resulting synaptic current must compete with the noisy spontaneous synaptic barrage for control of postsynaptic SNr neurons, which have their own frequency-dependent sensitivities. Despite this, SNr neurons subjected to synaptic conductance changes generated from recorded GPe neuron firing patterns also became coherent with oscillations over a broad range of frequencies. The presynaptic, synaptic, and postsynaptic frequency sensitivities were all dependent on the firing rates of presynaptic and postsynaptic neurons. Firing rate changes, often assumed to be the propagating signal in these circuits, do not encode most oscillation frequencies, but instead determine which signal frequencies propagate effectively and which are suppressed.SIGNIFICANCE STATEMENT Oscillations are present in all the basal ganglia nuclei, include a range of frequencies, and change over the course of learning and behavior. Exaggerated oscillations are a hallmark of basal ganglia pathologies, and each has a specific frequency range. Because of its position as a hub in the basal ganglia circuitry, the globus pallidus is a candidate origin for oscillations propagating between nuclei. We imposed low-amplitude oscillations on individual globus pallidus neurons at specific frequencies and measured the coherence between the oscillation and firing as a function of frequency. We then used these responses to measure the effectiveness of oscillatory propagation to other basal ganglia nuclei. Propagation was effective for oscillation frequencies as high as 100 Hz.

Principles of large-scale neural interactions

What mechanisms underlie flexible inter-areal communication in the cortex? We consider four mechanisms for temporal coordination and their contributions to communication: (1) Oscillatory synchronization (communication-through-coherence); (2) communication-through-resonance; (3) non-linear integration; and (4) linear signal transmission (coherence-through-communication). We discuss major challenges for communication-through-coherence based on layer- and cell-type-specific analyses of spike phase-locking, heterogeneity of dynamics across networks and states, and computational models for selective communication. We argue that resonance and non-linear integration are viable alternative mechanisms that facilitate computation and selective communication in recurrent networks. Finally, we consider communication in relation to cortical hierarchy and critically examine the hypothesis that feedforward and feedback communication use fast (gamma) and slow (alpha/beta) frequencies, respectively. Instead, we propose that feedforward propagation of prediction errors relies on the non-linear amplification of aperiodic transients, whereas gamma and beta rhythms represent rhythmic equilibrium states that facilitate sustained and efficient information encoding and amplification of short-range feedback via resonance.

Distinct Mechanisms Underlie Electrical Coupling Resonance and Its Interaction with Membrane Potential Resonance

Neurons in oscillatory networks often exhibit membrane potential resonance, a peak impedance at a non-zero input frequency. In electrically coupled oscillatory networks, the coupling coefficient (the ratio of post- and prejunctional voltage responses) could also show resonance. Such coupling resonance may emerge from the interaction between the coupling current and resonance properties of the coupled neurons, but this relationship has not been clearly described. Additionally, it is unknown if the gap-junction mediated electrical coupling conductance may have frequency dependence. We examined these questions by recording a pair of electrically coupled neurons in the oscillatory pyloric network of the crab Cancer borealis. We performed dual current- and voltage-clamp recordings and quantified the frequency preference of the coupled neurons, the coupling coefficient, the electrical conductance, and the postjunctional neuronal response. We found that all components exhibit frequency selectivity, but with distinct preferred frequencies. Mathematical and computational analysis showed that membrane potential resonance of the postjunctional neuron was sufficient to give rise to resonance properties of the coupling coefficient, but not the coupling conductance. A distinct coupling conductance resonance frequency therefore emerges either from other circuit components or from the gating properties of the gap junctions. Finally, to explore the functional effect of the resonance of the coupling conductance, we examined its role in synchronizing neuronal the activities of electrically coupled bursting model neurons. Together, our findings elucidate factors that produce electrical coupling resonance and the function of this resonance in oscillatory networks.

Neurodynamical Computing at the Information Boundaries of Intelligent Systems

Artificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies-properly conceived as reentrant dynamical flows and not merely as identified groups of neurons-may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.