Biology subjects

Plenz, D.

Publications and source records attributed to Plenz, D..

14 recordsLinked to original sources

bioRxiv2026

Glider compositionality and information capacity in an E/I-balanced neuronal automaton

In cellular automata, localized activity patterns called gliders propagate and interact to carry and transform information. Whether neuronal networks can harness this computational power remains unclear. Here, we demonstrate that a cortical network model with separate excitatory and inhibitory populations, graded cellular activity and uniform local connectivity spontaneously generates diverse, interacting gliders. An analytical reduction identifies the cellular conditions sustaining propagation of the dominant G-glider. Distinct gliders can assemble into growing structures that emit other glider types. Near excitation/inhibition balance, sparse glider dynamics coexist with high computational capacity, measured by input differentiation and generalization, with local capacity varying across space and time. Strong mutual inhibition between interneurons instead permits metastatic proliferation with low computational capacity. These findings connect cellular automata to neuronal information processing and identify interacting gliders as a candidate mechanism for dynamic plasticity: the reorganization of computation within an unchanged synaptic architecture.

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bioRxiv2026

Critical scaling of cortical ensembles without cooperative amplification

Cortical neurons are sparsely and weakly connected, motivating the long-standing idea that they must act collectively, as cell assemblies, to exert substantial influence on surrounding networks. Yet a few spikes in a single pyramidal neuron can recruit thousands of cortical neurons according to a power law with exponent ~0.285, consistent with a two-dimensional system near a critical percolation transition. Here we holographically stimulated ensembles of 1 to 16 layer 2/3 pyramidal neurons in visual cortex of awake mice while imaging hundreds of neighbouring neurons. Across two orders of magnitude in evoked spike count, network responses followed the same scaling law observed for single-neuron perturbations, with no detectable threshold at which co-activation produced additional amplification. Recruitment was sublinear, suppression increased with ensemble size, and ongoing scale-free avalanche dynamics remained stationary. Nevertheless, ensemble identity became increasingly decodable from surrounding activity. Thus, coordinated firing increases representational specificity without escaping the critical dynamics governing propagation: cortical ensembles convey identity without gaining disproportionate causal impact.

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bioRxiv2024

Critical Scaling of Novelty in the Cortex

The ability to detect and transmit novel events is essential for adaptive behavior in uncertain environments. Here, we investigate how holographically triggered, unanticipated action potentials propagate through the primary visual cortex of resting mice, focusing on pyramidal neuron communication. We find that these novel spikes -- uncorrelated with ongoing activity -- exert a disproportionately large influence on neighboring neurons, whose response scales as a power law (exponent [~]0.2-0.3). Even a few such spikes can recruit a large fraction of the local network, enabling robust decoding of perturbation origin despite high trial-by-trial variability and ongoing activity dominated by large activity fluctuations in the form of scale-invariant, parabolic neuronal avalanches. Simulations confirm this scaling to small, local perturbations aligns with the high susceptibility of complex systems near criticality. These results suggest that critical dynamics facilitate efficient transmission of novel signals, revealing a fundamental mechanism for cortical novelty detection.

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bioRxiv2024

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches--scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent,{chi} = 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally,{chi} is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores{chi} = 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies{chi} = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common crackling noise approach fails to determine{chi} under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.

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bioRxiv2022

Parabolic avalanche scaling in the synchronization of cortical cell assemblies

Neurons in cortex synchronize their spiking in response to local and distant inputs. These synchronized assemblies are fundamental to cortex function, yet basic dynamical aspects about their size and duration are largely unknown. Using 2-photon imaging of neurons in superficial cortex of awake mice, we show that synchronized assemblies organize as scale-invariant avalanches that quadratically grow with duration. This quadratic expansion was found only for correlated neurons and required temporal coarse graining to compensate for spatial subsampling when network dynamics are critical, as demonstrated in simulations. The corresponding time course of an inverted parabola with exponent of {chi} = 2 described avalanches of up to 5 s duration and maximized temporal complexity in the ongoing activity of prefrontal and somatosensory cortex and in visual responses of primary visual cortex. Our results identify a scale-invariant order in the synchronization of highly diverse cortical cell assemblies in the form of parabolic avalanches. Significance StatementThe synchronization of cell assemblies is fundamental to many brain theories. Here we show such synchronization to grow according to an inverted parabola that maximizes temporal complexity. This quadratic scaling found for cell assemblies of highly diverse size and duration is in line with prediction for neuronal avalanches and the cortex being in a critical state.

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bioRxiv2022

Variability of wheel running behavior in mice is dependent on housing, sex, and genetic background

Environmental enrichment (EE) has been increasingly used to enhance and support the physiological fitness and natural behavior of research animals. For mice, which are known to be highly active nocturnal animals that live in large social groups, the introduction of running wheels is a particularly promising approach in EE. When wheels are introduced to their home cage, mice increase their nocturnal locomotion activity by orders of magnitude. However, little is known about how mice share such a readily adopted EE. Here, we studied wheel running in single-housed and group-housed mice. We hypothesized that group-housed mice will compete over the scarce resource of a running wheel leading to a change in overall wheel usage compared to single-housed mice that have exclusive wheel access. We measured wheel locomotion in two strains of single-housed and group-housed mice over multiple 24h periods at sub-second temporal resolution using a custom-designed data acquisition system. We observed both sex- and housing-specific differences in wheel usage. In single-housed C57Bl/6 mice, mice ran at consistent speeds and females ran larger distances. In group housing, periods of slow locomotion speeds as well as speed transitions emerged with fewer breaks in wheel usage. This group effect was less pronounced in a genetic mouse model (parvalbumin-Cre on C57Bl/6 background). Our results demonstrate a change in wheel usage during group housing which supports competition over EE resources while enhancing overall locomotion in mice.

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bioRxiv2022

Oligodendrocyte-mediated Myelin Plasticity and its role in Neural Synchronization

Temporal synchrony of signals arriving from different neurons or brain regions is essential for proper neural processing. Nevertheless, it is not well understood how such synchrony is achieved and maintained in a complex network of time-delayed neural interactions. Myelin plasticity has been suggested as an efficient mechanism for controlling timing in brain communications through adaptive changes of axonal conduction velocity and consequently conduction time delays, or latencies; however, local rules and feedback mechanisms that oligodendrocytes (OL) use to achieve synchronization are not known. We propose a mathematical model of oligodendrocyte-mediated myelin plasticity (OMP) in which OL play an active role in providing such feedback. This is achieved without using arrival times at the synapse or modulatory signaling from astrocytes; instead, it relies on the presence of global and transient OL responses to local action potentials in the axons they myelinate. While inspired by OL morphology, we provide the theoretical underpinnings that motivated the model and explore its performance for a wide range of its parameters. Our results indicate that when the characteristic time of OLs spike responses is between 10 and 40 ms and the firing rates in individual axons are relatively low ([lap] 10 Hz), the OMP model efficiently synchronizes correlated and time-locked signals while latencies in axons carrying independent signals are unaffected. This suggests a novel form of selective synchronization in the CNS in which oligodendrocytes play an active role by modulating the conduction delays of correlated spike trains as they traverse to their targets. Significance StatementSynchronization of signals arriving from different neurons or brain regions is of great importance for proper brain function. In vertebrates, myelination provides an efficient way to achieve this by adjusting the conduction velocity and consequently the conduction delays. It is increasingly evident that myelination is an adaptive process and involved in learning; however, the local rules and the feedback that guide oligodendrocytes towards achieving desired delays are not known. Here we propose a simple and biologically plausible model of myelin plasticity in which oligodendrocytes play an active role in providing the needed feedback. We use theoretical arguments, mathematical modeling and computer simulations to show its robust synchronization capabilities which enable efficient communication between the brain regions.

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bioRxiv2022

Alpha rhythm induces attenuation-amplification dynamics in neural activity cascades

The alpha rhythm is a distinctive feature of the awake resting-state of the human brain. Recent evidence suggests that alpha plays an active role in information processing, modulating behavioral and cognitive performance. However, the functional role of alpha oscillations in the resting-state neuronal dynamics remains poorly understood. To address this question, we investigate collective neural activity during resting wake and NREM sleep, a physiologic state with marginal presence of alpha rhythm. We show that, during resting wake, alpha oscillations drive an alternation of attenuation and amplification bouts in neural activity. Our analysis indicates that inhibition is activated in pulses that last a single alpha cycle and gradually suppress neural activity, while excitation is successively enhanced over timescales of a few alpha cycles to amplify neural activity. Furthermore, we show that long-term, intermittent fluctuations in alpha amplitude--known as the "waxing and waning" phenomenon--are associated with an attenuation-amplification mechanism acting over the timescales of several seconds and described by a power law decay of the activity rate in the "waning" phase. Importantly, we do not observe such dynamics during NREM sleep. The results suggest that the alpha rhythm acts as a "pacemaker" for the alternation of inhibition and excitation bouts across multiple timescales, the "waxing and waning" being a long-term control mechanism of cortical excitability. The amplification regime observed beyond the timescales of the individual alpha cycle suggests in turn that alpha oscillations might modulate the intensity of neural activity not only through pulses of inhibition, as proposed in the pulsed inhibition hypothesis, but also by timely enhancing excitation (or dis-inhibition).

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bioRxiv2020

Scale-free dynamics in animal groups and brain networks

Collective phenomena fascinate by the emergence of order in systems composed of a myriad of small entities. They are ubiquitous in nature and can be found over a vast range of scales in physical and biological systems. Their key feature is the seemingly effortless emergence of adaptive collective behavior that cannot be trivially explained by the properties of the systems individual components. This perspective focuses on recent insights into the similarities of correlations for two apparently disparate phenomena: flocking in animal groups and neuronal ensemble activity in the brain. We first will summarize findings on the spontaneous organization in bird flocks and macro-scale human brain activity utilizing correlation functions and insights from critical dynamics. We then will discuss recent experimental findings that apply these approaches to the collective response of neurons to visual and motor processing, i.e. to local perturbations of neuronal networks at the meso- and microscale. We show how scale-free correlation functions capture the collective organization of neuronal avalanches in evoked neuronal populations in nonhuman primates and between neurons during visual processing in rodents. These experimental findings suggest that the coherent collective neural activity observed at scales much larger than the length of the direct neuronal interactions is demonstrative of a phase transition. We discuss the experimental support for either discontinuous or continuous phase transitions. We conclude that at or near a phase-transition neuronal information can propagate in the brain with the same efficiency as proposed to occur in the collective adaptive response observed in some animal groups.

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bioRxiv2020

Long-term stability of avalanche scaling and integrative network organization in prefrontal and premotor cortex

Ongoing neuronal activity in the cortex establishes functional networks of synchronization that reflect normal and pathological brain function. The reconstruction of these networks typically suffers from the use of indirect measures of neuronal activity at low spatiotemporal resolution and a lack of longitudinal tracking. Accordingly, the precise nature of the underlying synchronization dynamics and its translation into robust graph theoretical markers are not well characterized. Here, we studied the stability of cortical dynamics and reconstructed functional networks over many weeks in prefrontal and premotor cortex of awake nonhuman primates. We monitored neuronal population activity directly in the ongoing local field potential (LFP) at high spatial and temporal resolution using chronically implanted high-density microelectrode arrays. Ongoing activity was composed of neuronal avalanches exhibiting stable, inverted parabolic profiles with the collapse exponent of 2 in line with a critical branching process. Avalanche-based functional networks, reconstructed using a Normalized Count estimator, revealed robust integrative properties characterized by high neighborhood overlap between strongly connected nodes and robustness to weak-link pruning. "Entropy of mixing" analysis demonstrated progressive link reorganization over weeks. The long-term stability of avalanche scaling and integrative network organization should support the development of robust biomarkers to characterize normal and abnormal brain function.

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bioRxiv2020

Selective participation of single cortical neurons in neuronal avalanches

Neuronal avalanches are scale-invariant neuronal population activity patterns in cortex that emerge in vivo in the awake state and in vitro during balanced excitation and inhibition. Theory and experiments suggest that avalanches indicate a state of cortex that improves numerous aspects of information processing by allowing for the transient and selective formation of local as well as system-wide spanning neuronal groups. If avalanches are indeed involved with information processing, one might expect that particular single neurons would participate in particular avalanche patterns selectively. Alternatively, all neurons could participate with equal likelihood in each avalanche as would be expected for a population rate code. Distinguishing these hypotheses, however, has been difficult as robust avalanche analysis requires technically challenging measures of their intricate organization in space and time at the population level, while also recording sub- or suprathreshold activity from individual neurons with high temporal resolution. Here we identify repeated avalanches in the ongoing local field potential (LFP) measured with high-density microelectrode arrays in the cortex of awake nonhuman primates and in acute cortex slices from rats. We studied extracellular unit firing in vivo and intracellular responses of pyramidal neurons in vitro. We found that single neurons participate selectively in specific LFP-based avalanche patterns. Furthermore, we show in vitro that manipulating the balance of excitation and inhibition abolishes this selectivity. Our results support the view that avalanches represent the selective, scale-invariant formation of neuronal groups in line with the idea of Hebbian cell assemblies underlying cortical information processing.

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bioRxiv2020

Trial-by-trial variability in cortical responses exhibits scaling in spatial correlations predicted from critical dynamics

Simple sensory stimuli or motor outputs engage large populations of neurons in the mammalian cortex. When stimuli or outputs repeat, the robust population response contrasts with fluctuating responses of individual neurons, known as trial-by-trial variability. To understand this apparent discrepancy, a detailed identification of the underlying spatiotemporal correlations is required. Here, we analyze spatial correlations in the instantaneous fluctuations between neurons relative to the neuronal population. Using 2-photon imaging of visual and auditory responses in primary cortices of awake mice, we show that these correlations grow linearly with the size of the observed cortical area. We extend these observations to the cortical mesoscale by analyzing local field potentials in behaving nonhuman primates. In network simulations, we demonstrate this linear growth in spatial correlation to emerge at criticality. Our findings suggest that trial-by-trial variability is a signature of critical dynamics in cortex maintaining robust, long-range spatial correlations among neurons.

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bioRxiv2019

The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ-oscillations

Activity cascades are found in many complex systems. In the cortex, they arise in the form of neuronal avalanches that capture ongoing and evoked neuronal activities at many spatial and temporal scales. The scale-invariant nature of avalanches suggests that the brain is in a critical state, yet predictions from critical theory on the temporal unfolding of avalanches have yet to be confirmed in vivo. Here we show in awake nonhuman primates that the temporal profile of avalanches follows a symmetrical, inverted parabola spanning up to hundreds of milliseconds. This parabola constrains how avalanches initiate locally, extend spatially and shrink as they evolve in time. Importantly, parabolas of different durations can be collapsed with a scaling exponent close to 2 supporting critical generational models of neuronal avalanches. Spontaneously emerging, transient {gamma}-oscillations coexist with and modulate these avalanche parabolas thereby providing a temporal segmentation to inherently scale-invariant, critical dynamics. Our results identify avalanches and oscillations as dual principles in the temporal organization of brain activity.\n\nSignificance StatementThe most common framework for understanding the temporal organization of brain activity is that of oscillations, or brain waves. In oscillations, distinct physiological frequencies emerge at well-defined temporal scales, dividing brain activity into time segments underlying cortex function. Here, we identify a fundamentally different temporal parsing of activity in cortex. In awake Macaque monkeys, we demonstrate the motif of an inverted parabola that governs the temporal unfolding of brain activity in the form of neuronal avalanches. This symmetrical motif is scale-invariant, that is, it is not tied to time segments, and exhibits a scaling exponent close to 2, in line with prediction from theory of critical systems. We suggest that oscillations provide a transient regularity in an otherwise scale-invariant temporal organization pervading cortical activity at numerous scales.

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bioRxiv2019

Neuronal avalanches in input and associative layers of auditory cortex

The primary auditory cortex processes acoustic sequences for the perception of behaviorally meaningful sounds such as speech. Sound information arrives at its input layer 4 from where activity propagates to associative layer 2/3. It is currently not known whether there is a particular organization of neuronal population activity that is stable across layers and sound levels during sound processing. We used in vivo 2-photon imaging of pyramidal neurons in cortical layers L4 and L2/3 of mouse A1 to characterize the populations of neurons that were active spontaneously, i.e. in the absence of a sound stimulus, and those recruited by single-frequency tonal stimuli at different sound levels. Single-frequency sounds recruited neurons of widely ranging frequency selectivity in both layers. We defined neural ensembles as neurons being active within or during successive temporal windows at the temporal resolution of our imaging. For both layers, neuronal ensembles were highly variable in size during spontaneous activity as well as during sound presentation. Ensemble sizes distributed according to power laws, the hallmark of neuronal avalanches, and were similar across sound levels. Avalanches activated by sound were composed of neurons with diverse tuning preference, yet with selectivity independent of avalanche size. Thus, spontaneous and evoked activity in both L4 and L2/3 of A1 are composed of neuronal avalanches with similar power law relationships. Our results demonstrate network principles linked to maximal dynamic range, optimal information transfer and matching complexity between L4 and L2/3 to shape population activity in auditory cortex.

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