Neural entrainment has become a phenomenon of exceptional interest to neuroscience, given its involvement in rhythm perception, production, and overt synchronized behavior. Yet, traditional methods fail to quantify neural entrainment due to a misalignment with its fundamental definition (e.g., see Novembre and Iannetti, 2018; Rajandran and Schupp, 2019). The definition of entrainment assumes that endogenous oscillatory brain activity undergoes dynamic frequency adjustments to synchronize with environmental rhythms (Lakatos et al., 2019). Following this definition, we recently developed a method sensitive to this process. Our aim was to isolate from the electroencephalographic (EEG) signal an oscillatory component that is attuned to the frequency of a rhythmic stimulation, hypothesizing that the oscillation would adaptively speed up and slow down to achieve stable synchronization over time. To induce and measure these adaptive changes in a controlled fashion, we developed the event-related frequency adjustment (ERFA) paradigm (Rosso et al., 2023). A total of twenty healthy participants took part in our study. They were instructed to tap their finger synchronously with an isochronous auditory metronome, which was unpredictably perturbed by phase-shifts and tempo-changes in both positive and negative directions across different experimental conditions. EEG was recorded during the task, and ERFA responses were quantified as changes in instantaneous frequency of the entrained component. Our results indicate that ERFAs track the stimulus dynamics in accordance with the perturbation type and direction, preferentially for a sensorimotor component. The clear and consistent patterns confirm that our method is sensitive to the process of frequency adjustment that defines neural entrainment. In this Virtual Journal Club, the discussion of our findings will be complemented by methodological insights beneficial to researchers in the fields of rhythm perception and production, as well as timing in general. We discuss the dos and don’ts of using instantaneous frequency to quantify oscillatory dynamics, the advantages of adopting a multivariate approach to source separation, the robustness against the confounder of responses evoked by periodic stimulation, and provide an overview of domains and concrete examples where the methodological framework can be applied.

To understand neural computation and the dynamics in the brain, we usually focus on the connectivity among neurons. In contrast, the properties of single neurons are often thought to be negligible, at least as far as the activity of networks is concerned. In this talk, I will contradict this notion and demonstrate how the biophysics of action-potential generation can have a decisive impact on network behaviour. Our recent theoretical work shows that, among regularly firing neurons, the somewhat unattended homoclinic type (characterized by a spike onset via a saddle homoclinic orbit bifurcation) particularly stands out: First, spikes of this type foster specific network states - synchronization in inhibitory and splayed-out/frustrated states in excitatory networks. Second, homoclinic spikes can easily be induced by changes in a variety of physiological parameters (like temperature, extracellular potassium, or dendritic morphology). As a consequence, such parameter changes can even induce switches in network states, solely based on a modification of cellular voltage dynamics. I will provide first experimental evidence and discuss functional consequences of homoclinic spikes for the design of efficient pattern-generating motor circuits in insects as well as for mammalian pathologies like febrile seizures. Our analysis predicts an interesting role for homoclinic action potentials as an integral part of brain dynamics in both health and disease.

The visual system of the brain is highly parallel in its architecture. This is clearly evident in the outputs of the retina, which arise from neurons called ganglion cells. Work in our lab has shown that mammalian retinas contain more than a dozen distinct types of ganglion cells. Each type appears to filter the retinal image in a unique way and to relay this processed signal to a specific set of targets in the brain. My students and I are working to understand the meaning of this parallel organization through electrophysiological and anatomical studies. We record from light-responsive ganglion cells in vitro using the whole-cell patch method. This allows us to correlate directly the visual response properties, intrinsic electrical behavior, synaptic pharmacology, dendritic morphology and axonal projections of single neurons. Other methods used in the lab include neuroanatomical tracing techniques, single-unit recording and immunohistochemistry. We seek to specify the total number of ganglion cell types, the distinguishing characteristics of each type, and the intraretinal mechanisms (structural, electrical, and synaptic) that shape their stimulus selectivities. Recent work in the lab has identified a bizarre new ganglion cell type that is also a photoreceptor, capable of responding to light even when it is synaptically uncoupled from conventional (rod and cone) photoreceptors. These ganglion cells appear to play a key role in resetting the biological clock. It is just this sort of link, between a specific cell type and a well-defined behavioral or perceptual function, that we seek to establish for the full range of ganglion cell types. My research concerns the structural and functional organization of retinal ganglion cells, the output cells of the retina whose axons make up the optic nerve. Ganglion cells exhibit great diversity both in their morphology and in their responses to light stimuli. On this basis, they are divisible into a large number of types (>15). Each ganglion-cell type appears to send its outputs to a specific set of central visual nuclei. This suggests that ganglion cell heterogeneity has evolved to provide each visual center in the brain with pre-processed representations of the visual scene tailored to its specific functional requirements. Though the outline of this story has been appreciated for some time, it has received little systematic exploration. My laboratory is addressing in parallel three sets of related questions: 1) How many types of ganglion cells are there in a typical mammalian retina and what are their structural and functional characteristics? 2) What combination of synaptic networks and intrinsic membrane properties are responsible for the characteristic light responses of individual types? 3) What do the functional specializations of individual classes contribute to perceptual function or to visually mediated behavior? To pursue these questions, we label retinal ganglion cells by retrograde transport from the brain; analyze in vitro their light responses, intrinsic membrane properties and synaptic pharmacology using the whole-cell patch clamp method; and reveal their morphology with intracellular dyes. Recently, we have discovered a novel ganglion cell in rat retina that is intrinsically photosensitive. These ganglion cells exhibit robust light responses even when all influences from classical photoreceptors (rods and cones) are blocked, either by applying pharmacological agents or by dissociating the ganglion cell from the retina. These photosensitive ganglion cells seem likely to serve as photoreceptors for the photic synchronization of circadian rhythms, the mechanism that allows us to overcome jet lag. They project to the circadian pacemaker of the brain, the suprachiasmatic nucleus of the hypothalamus. Their temporal kinetics, threshold, dynamic range, and spectral tuning all match known properties of the synchronization or "entrainment" mechanism. These photosensitive ganglion cells innervate various other brain targets, such as the midbrain pupillary control center, and apparently contribute to a host of behavioral responses to ambient lighting conditions. These findings help to explain why circadian and pupillary light responses persist in mammals, including humans, with profound disruption of rod and cone function. Ongoing experiments are designed to elucidate the phototransduction mechanism, including the identity of the photopigment and the nature of downstream signaling pathways. In other studies, we seek to provide a more detailed characterization of the photic responsiveness and both morphological and functional evidence concerning possible interactions with conventional rod- and cone-driven retinal circuits. These studies are of potential value in understanding and designing appropriate therapies for jet lag, the negative consequences of shift work, and seasonal affective disorder.

It has long been established that the hippocampus plays a crucial role for episodic memory. As opposed to the modular approach, now it is generally assumed that being a complex structure, the HC performs multiplex interconnected functions, whose hierarchical organization provides basis for the higher cognitive functions such as semantics-based encoding and retrieval. However, the «where, when and how» properties of distinct memory aspects within and outside the HC are still under debate. Here we used a visual associative memory task as a probe to test the hypothesis about the differential involvement of the rostral and caudal portions of the human hippocampus in memory encoding, recognition and associative recall. In epilepsy patients implanted with stereo-EEG, we show that at retrieval the rostral HC is selectively active for recognition memory, whereas the caudal HC is selectively active for the associative memory. Low frequency desynchronization and high frequency synchronization characterize the temporal dynamic in encoding and retrieval. Therefore, we describe here anatomical segregation in the hippocampal contributions to associative and recognition memory.

Coping with threatening situations requires both identifying stimuli predicting danger and selecting adaptive behavioral responses in order to survive. The dorso medial prefrontal cortex (dmPFC) is a critical structure involved in the regulation of threat-related behaviour, yet it is still largely unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks in order to successfully drive adaptive responses. Over the past years, we used a combination we used a combination of extracellular recordings, neuronal decoding approaches, and state of the art optogenetic manipulations to identify key neuronal elements and mechanisms controlling defensive fear responses. I will present an overview of our recent work ranging from analyses of dedicated neuronal types and oscillatory and synchronization mechanisms to artificial intelligence approaches used to decode the activity or large population of neurons. Ultimately these analyses allowed the identification of high dimensional representations of defensive behavior unfolding within prefrontal networks.

Flow is defined as an altered state of consciousness with excessive attention and enormous sense of pleasure, when engaged in a challenging task, first postulated by a psychologist, the late M. Csikszentmihayli. The main focus of this talk will be “Team Flow,” but there were two lines of previous studies in our laboratory as its background. First is inter-body and inter-brain coordination/synchrony between individuals. Considering various rhythmic echoing/synchronization phenomena in animal behavior, it could be regarded as the biological, sub-symbolic and implicit origin of social interactions. The second line of precursor research is on the state of Solo Flow in game playing. We employed attenuation of AEP (Auditory Evoked Potential) to task-irrelevant sound probes as an objective-neural indicator of such a Flow status, and found that; 1) Mutual link between the ACC & the TP is critical, and 2) overall, top-down influence is enhanced while bottom-up causality is attenuated. Having these as the background, I will present our latest study of Team Flow in game playing. We found that; 3) the neural correlates of Team Flow is distinctively different from those of Solo Flow nor of non-flow social, 4) the left medial temporal cortex seems to form an integrative node for Team Flow, receiving input related to Solo Flow state from the right PFC and input related to social state from the right IFC, and 5) Intra-brain (dis)similarity of brain activity well predicts (dis)similarity of skills/cognition as well as affinity for inter-brain coherence.

The brain exhibits a rich repertoire of oscillatory patterns organized in space, time and frequency. However, despite ever more-detailed characterizations of spectrally-resolved network patterns, the principles governing oscillatory activity at the system-level remain unclear. Here, we propose that the transient emergence of spatially organized brain rhythms are signatures of weakly stable synchronization between subsets of brain areas, naturally occurring at reduced collective frequencies due to the presence of time delays. To test this mechanism, we build a reduced network model representing interactions between local neuronal populations (with damped oscillatory response at 40Hz) coupled in the human neuroanatomical network. Following theoretical predictions, weakly stable cluster synchronization drives a rich repertoire of short-lived (or metastable) oscillatory modes, whose frequency inversely depends on the number of units, the strength of coupling and the propagation times. Despite the significant degree of reduction, we find a range of model parameters where the frequencies of collective oscillations fall in the range of typical brain rhythms, leading to an optimal fit of the power spectra of magnetoencephalographic signals from 89 heathy individuals. These findings provide a mechanistic scenario for the spontaneous emergence of frequency-specific long-range phase-coupling observed in magneto- and electroencephalographic signals as signatures of resonant modes emerging in the space-time structure of the Connectome, reinforcing the importance of incorporating realistic time delays in network models of oscillatory brain activity.

Inter-areal coherence between cortical field-potentials is a widespread phenomenon and depends on numerous behavioral and cognitive factors. It has been hypothesized that inter-areal coherence reflects phase-synchronization between local oscillations and flexibly gates communication. We reveal an alternative mechanism, where coherence results from and is not the cause of communication, and naturally emerges as a consequence of the fact that spiking activity in a sending area causes post-synaptic inputs both in the same area and in other areas. Consequently, coherence depends in a lawful manner on oscillatory power and phase-locking in a sending area and inter-areal connectivity. We show that changes in oscillatory power explain prominent changes in fronto-parietal beta-coherence with movement and memory, and LGN-V1 gamma-coherence with arousal and visual stimulation. Optogenetic silencing of a receiving area and E/I network simulations demonstrate that afferent synaptic inputs rather than spiking entrainment are the main determinant of inter-areal coherence. These findings suggest that the unique spectral profiles of different brain areas automatically give rise to large-scale inter-areal coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.

The interaction between spontaneously and externally evoked neuronal activity is fundamental for a functional brain. Increasing evidence suggests that bursts of high-power oscillations in the 15-30 Hz beta-band represent activation of resting state networks and can mask perception of external cues. Yet demonstration of the effect of beta power modulation on perception in real-time is missing, and little is known about the underlying mechanism. In this talk I will present the methods we developed to fill this gap together with our recent results. We used a closed-loop stimulus-intensity adjustment system based on online burst-occupancy analyses in rats involved in a forepaw vibrotactile detection task. We found that the masking influence of burst-occupancy on perception can be counterbalanced in real-time by adjusting the vibration amplitude. Offline analysis of firing-rates and local field potentials across cortical layers and frequency bands confirmed that beta-power in the somatosensory cortex anticorrelated with sensory evoked responses. Mechanistically, bursts in all bands were accompanied by transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction of firing-rate. Our closed loop approach reveals that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.

Being fundamentally a non-equilibrium process, synchronization comes with unavoidable energy costs and has to be maintained under the constraint of limited resources. Such resource constraints are often reflected as a finite coupling budget available in a network to facilitate interaction and communication. In this talk, I will show that introducing temporal variation in the network structure can lead to efficient synchronization even when stable synchrony is impossible in any static network under the given budget. Our strategy is based on an open-loop control scheme and alludes to a fundamental advantage of temporal networks. Whether this advantage of temporality can be utilized in the brain is an interesting open question.

The CNS is responsive to an ever-changing environment. Until recently, studies of neural plasticity focused almost exclusively on functional and structural changes of neuronal synapses. In recent years, myelin plasticity has emerged as a potential modulator of neural networks. Myelination of previously unmyelinated axons, and changes in the structure on already-myelinated axons, can have large effects on network function. The heterogeneity of the extent of how axons in the CNS are myelinated offers diverse scope for dynamic myelin changes to fine-tune neural circuits. The traditionally held view of myelin as a passive insulator of axons is now changing to one of lifelong changes in myelin, modulated by neuronal activity and experience. Myelin, produced by oligodendrocytes (OLs), is essential for normal brain function, as it provides fast signal transmission, promotes synchronization of neuronal signals and helps to maintain neuronal function. OLs differentiate from oligodendrocyte precursor cells (OPCs), which are distributed throughout the adult brain, and myelination continues into late adulthood. OPCs can sense neuronal activity as they receive synaptic inputs from neurons and express voltage-gated ion channels and neurotransmitter receptors, and differentiate into myelinating OLs in response to changes in neuronal activity. This lecture will explore to what extent myelin plasticity occurs in adult animals, whether myelin changes occur in non-motor learning tasks, especially in learning and memory, and questions whether myelin plasticity and myelin regeneration are two sides of the same coin.

A basic time scale in neural dynamics from single cells to the network level is the membrane time constant - set by a neuron’s input resistance and its capacitance. Interestingly, the membrane capacitance appears to be more dynamic than previously assumed with implications for neural function and pathology. Indeed, altered membrane capacitance has been observed in reaction to physiological changes like neural swelling, but also in ageing and Alzheimer's disease. Importantly, according to theory, even small changes of the capacitance can affect neuronal signal processing, e.g. increase network synchronization or facilitate transmission of high frequencies. In experiment, robust methods to modify the capacitance of a neuron have been missing. Here, we present the capacitance clamp - an electrophysiological method for capacitance control based on an unconventional application of the dynamic clamp. In its original form, dynamic clamp mimics additional synaptic or ionic conductances by injecting their respective currents. Whereas a conductance directly governs a current, the membrane capacitance determines how fast the voltage responds to a current. Accordingly, capacitance clamp mimics an altered capacitance by injecting a dynamic current that slows down or speeds up the voltage response (Fig 1 A). For the required dynamic current, the experimenter only has to specify the original cell and the desired target capacitance. In particular, capacitance clamp requires no detailed model of present conductances and thus can be applied in every excitable cell. To validate the capacitance clamp, we performed numerical simulations of the protocol and applied it to modify the capacitance of cultured neurons. First, we simulated capacitance clamp in conductance based neuron models and analysed impedance and firing frequency to verify the altered capacitance. Second, in dentate gyrus granule cells from rats, we could reliably control the capacitance in a range of 75 to 200% of the original capacitance and observed pronounced changes in the shape of the action potentials: increasing the capacitance reduced after-hyperpolarization amplitudes and slowed down repolarization. To conclude, we present a novel tool for electrophysiology: the capacitance clamp provides reliable control over the capacitance of a neuron and thereby opens a new way to study the temporal dynamics of excitable cells.

Long-range projections link distant circuits in the brain, allowing efficient transfer of information between regions and synchronization of distributed patterns of neural activity. Understanding the functional roles of defined neuronal projection pathways requires temporally precise manipulation of their activity, and optogenetic tools appear to be an obvious choice for such experiments. However, we and others have previously shown that commonly-used inhibitory optogenetic tools have low efficacy and off-target effects when applied to presynaptic terminals. In my talk, I will present a new solution to this problem: a targeting-enhanced mosquito homologue of the vertebrate encephalopsin (eOPN3), which upon activation can effectively suppress synaptic transmission through the Gi/o signaling pathway. Brief illumination of presynaptic terminals expressing eOPN3 triggers a lasting suppression of synaptic output that recovers spontaneously within minutes in vitro and in vivo. The efficacy of eOPN3 in suppressing presynaptic release opens new avenues for functional interrogation of long-range neuronal circuits in vivo.

When listening to music, we typically lock onto and move to a beat (1-6 Hz). Behavioral studies on such synchronization (Repp 2005) abound, yet the neural mechanisms remain poorly understood. Some models hypothesize an array of self-sustaining entrainable neural oscillators that resonate when forced with rhythmic stimuli (Large et al. 2010). In contrast, our formulation focuses on event time estimation and plasticity: a neuronal beat generator that adapts its intrinsic frequency and phase to match the extermal rhythm. The model quickly learns new rhythms, within a few cycles as found in human behavior. When the stimulus is removed the beat generator continues to produce the learned rhythm in accordance with a synchronization continuation task.

The subdivision benefit refers to the positive effect of subdividing a beat on sensorimotor synchronization. We recorded electroencephalograms of musicians and non-musicians to study how they listened or finger-tapped to a beat, subdivided into four distinct subdivisions. Musicians showed more consistent tapping responses than non-musicians, and enhanced neural entrainment during the tapping task than in the listening task. In both groups, there was a neural enhancement of the beat frequency and its first harmonic (related to duplets) after listening to the four subdivisions. Furthermore, non-musicians tapped more consistently to the beat of duplets than other subdivisions. Altogether, this suggests a neural and behavioral advantage for binary subdivisions, that can be modulated with formal training in music.

The vIRt nucleus in the medulla, composed of mainly inhibitory neurons, is necessary for whisking rhythm generation. It innervates motoneurons in the facial nucleus (FN) that project to intrinsic vibrissa muscles. The nearby pre-Bötzinger complex (pBötC), which generates inhalation, sends inhibitory inputs to the vIRt nucleus which contribute to the synchronization of vIRt neurons. Lower-amplitude periodic whisking, however, can occur after decay of the pBötC signal. To explain how vIRt network generates these “intervening” whisks by bursting in synchrony, and how pBötC input induces strong whisks, we construct and analyze a conductance-based (CB) model of the vIRt circuit composed of hypothetical two groups, vIRtr and vIRtp, of bursting inhibitory neurons with spike-frequency adaptation currents and constant external inputs. The CB model is reduced to a rate model to enable analytical treatment. We find, analytically and computationally, that without pBötC input, periodic bursting states occur within a certain ranges of network connectivities. Whisk amplitudes increase with the level constant external input to the vIRT. With pBötC inhibition intact, the amplitude of the first whisk in a breathing cycle is larger than the intervening whisks for large pBötC input and small inhibitory coupling between the vIRT sub-populations. The pBötC input advances the next whisk and shortens its amplitude if it arrives at the beginning of the whisking cycle generated by the vIRT, and delays the next whisks if it arrives at the end of that cycle. Our theory provides a mechanism for whisking generation and reveals how whisking frequency and amplitude are controlled.

Neural codes, such as temporal codes (precisely timed spikes) and rate codes (instantaneous spike firing rates), are believed to be used in encoding sensory information into spike trains of cortical neurons. Temporal and rate codes co-exist in the spike train and such multiplexed neural code-carrying spike trains have been shown to be spatially synchronized in multiple neurons across different cortical layers during sensory information processing. Inhibition is suggested to promote such synchronization, but it is unclear whether distinct subtypes of interneurons make different contributions in the synchronization of multiplexed neural codes. To test this, in vivo single-unit recordings from barrel cortex were combined with optogenetic manipulations to determine the contributions of parvalbumin (PV)- and somatostatin (SST)-positive interneurons to synchronization of precisely timed spike sequences. We found that PV interneurons preferentially promote the synchronization of spike times when instantaneous firing rates are low (<12 Hz), whereas SST interneurons preferentially promote the synchronization of spike times when instantaneous firing rates are high (>12 Hz). Furthermore, using a computational model, we demonstrate that these effects can be explained by PV and SST interneurons having preferential contribution to feedforward and feedback inhibition, respectively. Overall, these results show that PV and SST interneurons have distinct frequency (rate code)-selective roles in dynamically gating the synchronization of spike times (temporal code) through preferentially recruiting feedforward and feedback inhibitory circuit motifs. The inhibitory neural circuit mechanisms we uncovered here his may have critical roles in regulating neural code-based somatosensory information processing in the neocortex.

Firing-rate (FR) or neural-mass models are widely used for studying computations performed by neural populations. Despite their success, classical firing-rate models do not capture spike timing effects on the microscopic level such as spike synchronization and are difficult to link to spiking data in experimental recordings. For large neuronal populations, the gap between the spiking neuron dynamics on the microscopic level and coarse-grained FR models on the population level can be bridged by mean-field theory formally valid for infinitely many neurons. It remains however challenging to extend the resulting mean-field models to finite-size populations with biologically realistic neuron numbers per cell type (mesoscopic scale). In this talk, I present a mathematical framework for mesoscopic populations of generalized integrate-and-fire neuron models that accounts for fluctuations caused by the finite number of neurons. To this end, I will introduce the refractory density method for quasi-renewal processes and show how this method can be generalized to finite-size populations. To demonstrate the flexibility of this approach, I will show how synaptic short-term plasticity can be incorporated in the mesoscopic mean-field framework. On the other hand, the framework permits a systematic reduction to low-dimensional FR equations using the eigenfunction method. Our modeling framework enables a re-examination of classical FR models in computational neuroscience under biophysically more realistic conditions.

MRI data quality is crucial to the result. This workshop talks some aspects we need to pay attention during the data acquisition, including FoV/slice brain coverage, synchronization between image acquisition and stimulus presentation, instruction to participant, real time quality monitoring, the usage of physiological data. Prior to the meeting, we are collecting questions for Xiangrui on anything related to mri protocol/parameters: https://www.tricider.com/admin/2YW93TsWZJ3/2DBkJUoE5Ot

Dravet syndrome is a severe childhood epilepsy due to heterozygous loss-of-function mutation of the gene SCN1A, which encodes the type 1 neuronal voltage gated sodium (Na+) channel alpha-subunit Nav1.1. Prior studies in mouse models of Dravet syndrome (Scn1a+/- mice) at early developmental time points indicate that, in cerebral cortex, Nav1.1 is predominantly expressed in GABAergic interneurons (INs) and, in particular, in parvalbumin-positive fast-spiking basket cells (PV-INs). This has led to a model of Dravet syndrome pathogenesis whereby Nav1.1 mutation leads to preferential IN dysfunction, decreased synaptic inhibition, hyperexcitability, and epilepsy. We found that, at later developmental time points, the intrinsic excitability of PV-INs has essentially normalized, via compensatory reorganization of axonal Na+ channels. Instead, we found persistent and seemingly paradoxical dysfunction of putative disinhibitory INs expressing vasoactive intestinal peptide (VIP-INs). In vivo two-photon calcium imaging in neocortex during temperature-induced seizures in Scn1a+/- mice showed that mean activity of both putative principal cells and PV-INs was higher in Scn1a+/- relative to wild-type controls during quiet wakefulness at baseline and at elevated core body temperature. However, wild-type PV-INs showed a progressive synchronization in response to temperature elevation that was absent in PV-INs from Scn1a+/- mice immediately prior to seizure onset. We suggest that impaired PV-IN synchronization, perhaps via persistent axonal dysfunction, may contribute to the transition to the ictal state during temperature induced seizures in Dravet syndrome.