Biology subjects

Pieper, F.

Publications and source records attributed to Pieper, F..

9 recordsLinked to original sources

bioRxiv2026

Redundant information across functionally coupled cortical networks supports rapid perceptual decisions in the ferret

Coordinated activity across cortical areas transforms sensory inputs into perceptual decisions, yet how task-relevant information is distributed across sites and linked to functional interactions and behavior remains unclear. Conventional functional connectivity measures reveal statistical dependencies between neural signals but cannot distinguish information encoded uniquely at individual sites, shared redundantly across sites, or available only from their joint activity. Here, we used Partial Information Decomposition (PID) to characterize stimulus information during fast and slow correct decisions. We analyzed local field potentials (LFPs) extracted from mesoscale electrocorticographic recordings from auditory, visual, and parietal cortices in ferrets performing a visual and audiovisual spatial-detection task. Time- and frequency-resolved analyses of local field potential power and phase showed that stimulus-side information was strongest in the theta and alpha bands and greater during fast than slow responses. PID applied to pairs of recording sites revealed that fast responses were associated with earlier and stronger unique information and a greater relative contribution of redundancy, whereas synergistic contributions were smaller. During fast responses, redundancy was selectively associated with stronger LFP power-envelope coupling. These findings indicate that faster perceptual decisions involve a frequency-specific reorganization of cortical information, characterized by early local encoding and enhanced redundant information across functionally interacting sites.

neuroscience↗

bioRxiv2024

Causal Interactions between Phase- and Amplitude-Coupling in Cortical Networks

Phase coherence and amplitude correlations across brain regions are two main mechanisms of connectivity that govern brain dynamics at multiple scales. However, despite the increasing evidence that associates these mechanisms with brain functions and cognitive processes, the relationship between these different coupling modes is not well understood. Here, we study the causal relation between both types of functional coupling across multiple cortical areas. While most of the studies adopt a definition based on pairs of electrodes or regions of interest, we here employ a multichannel approach that provides us with a time-resolved definition of phase and amplitude coupling parameters. Using data recorded with a multichannel {micro}ECoG array from the ferret brain, we found that the transmission of information between both modes can be unidirectional or bidirectional, depending on the frequency band of the underlying signal. These results were reproduced in magnetoencephalography (MEG) data recorded during resting from the human brain. We show that this transmission of information occurs in a model of coupled oscillators and may represent a generic feature of a dynamical system. Together, our findings open the possibility of a general mechanism that may govern multi-scale interactions in brain dynamics.

neuroscience↗

bioRxiv2023

Functional hierarchies in brain dynamics characterized by signal reversibility in ferret cortex

Brain signal irreversibility has been shown to be a promising approach to study neural dynamics. Nevertheless, the relation with cortical hierarchy and the influence of different electrophysiological features is not completely understood. In this study, we recorded local field potentials (LFPs) during spontaneous behavior, including awake and sleep periods, using custom micro-electrocorticographic (ECoG) arrays implanted in ferrets. In contrast to humans, ferrets remain less time in each state across the sleep-wake cycle. We deployed a diverse set of metrics in order to measure the levels of complexity of the different behavioral states. In particular, brain irreversibility, which allows us to quantify the level of non-equilibrium captured by the arrow of time of the signal, revealed the hierarchical organization of the ferrets cortex. We found different signatures of irreversibility and functional hierarchy of large-scale dynamics in three different brain states (active awake, quiet awake, and deep sleep), showing a lower level of irreversibility in the deep sleep stage, compared to the other. Irreversibility also allowed us to disentangle the influence of different brain regions and frequency bands in this process, showing a predominance of the parietal area and the theta band. Furthermore, when inspecting the embedded dynamic through a Hidden Markov Model, the deep sleep stage was revealed to have a lower switching rate and lower entropy production. These results suggest functional hierarchies in organization that can be revealed through thermodynamic features and information theory metrics.

neuroscience↗

bioRxiv2020

BiPOLES: a tool for bidirectional dual-color optogenetic control of neurons

Optogenetic manipulation of neuronal activity has become an indispensable experimental strategy in neuroscience research. A large repertoire of excitatory and inhibitory tools allows precise activation or inhibition of genetically targetable neuronal populations. However, an optogenetic tool for reliable bidirectional control of neuronal activity allowing both up- and downregulation of the same neurons in a single experiment is still missing. Here we report BiPOLES, an optogenetic tool for potent excitation and inhibition of the same population of neurons with light of two different colors. BiPOLES consists of an inhibitory, blue-light-sensitive anion-conducting channelrhodopsin fused to an excitatory, red-light-sensitive cation-conducting channelrhodopsin in a single, trafficking-optimized tandem protein. BiPOLES enables multiple new applications including potent dual-color spiking and silencing of the same neurons in vivo and dual-color optogenetic control of two independent neuronal populations.

neuroscience↗

bioRxiv2019

Large-scale functional connectivity in multisensory cortex predicts performance

Complex behavior and task execution require fast changes of local activity and functional connectivity in cortical networks at multiple scales. The roles that changes of power and connectivity play during these processes are still not well understood. Here, we study how fluctuations of functional cortical coupling across different brain areas determine performance in an audiovisual, lateralized detection task in the ferret. We hypothesized that dynamic variations in the networks state determine the animals performance. We evaluated these by quantifying changes of local power and of phase coupling across visual, auditory and parietal regions. While power for hit and miss trials showed significant differences only during stimulus and response onset, phase coupling already differed before stimulus onset. An analysis of principal components in coupling at the single-trial level during this period allowed us to reveal the subnetworks that most strongly determined performance. Whereas higher global phase coupling of visual and auditory regions to parietal cortex was predictive of task performance, a second component revealed a reduction in coupling between subnetworks of different sensory modalities, probably to allow a better detection of the unimodal signals. Furthermore, we observed that long-range coupling became more predominant during the task period compared to the pre-stimulus baseline. Taken together, our results show that fluctuations in the network state, as reflected in large-scale coupling, are key determinants of the animals behavior.

neuroscience↗

bioRxiv2019

Multi-frequency tACS has lasting effects on neural synchrony and audiovisual responses

BACKGROUND: In cortical networks, synchronized oscillatory activity of neuronal populations enables communication, and its disturbance is related to a range of pathologies. Transcranial alternating current stimulation (tACS) has been explored as a flexible, noninvasive tool for the modulation and restoration of synchronized oscillatory signals. While numerous studies have addressed cognitive or behavioural effects of electrical stimulation, the neural changes underlying the effects of tACS and their persistence after stimulation offset have remained unclear. OBJECTIVE: Here, we screened for lasting aftereffects of prolonged tACS on intrinsic network activity and audiovisual processing in the anesthetized ferret brain. METHODS: Electrical stimulation was applied via subcutaneous wire electrodes. Current waveforms were synthesized from two frequencies in the alpha or gamma range, respectively. Flashes and clicks were used for audiovisual stimulation. Electrocorticographic recordings from an extended network including occipital, temporal and parietal cortical areas were obtained before and after tACS. RESULTS: Changes in local synchrony (continuous and spike-triggered power of LFP), synchrony across recording sites (imaginary coherence) and altered dynamics of sensory response-features (peak-to-peak amplitude, extremum latency) following electrical stimulation consistently point to a synchronizing effect of tACS that can outlast stimulation offset by at least 10 min. Gamma-band tACS proved particularly effective. In line with previous reports on cross-frequency interactions, we observed effects on coherence and power of baseline activity at frequencies other than the ones targeted by tACS. These cross-frequency interactions appeared to underlie the strengthening and stabilizing effect on audiovisual responses. CONCLUSION: We demonstrate aftereffects of tACS on synchrony and stimulus processing in an extended cortical network, measured intracranially in a setting that resembles tACS stimulation in humans. The data provide direct evidence for the efficacy of tACS as a tool for sustained modulation of cortical network dynamics.

neuroscience↗

bioRxiv2019

Context-specific modulation of intrinsic coupling modes shapes multisensory processing

Intrinsically generated patterns of coupled neuronal activity are associated with the dynamics of specific brain states. Sensory inputs are extrinsic factors that can perturb these intrinsic coupling modes, creating a complex scenario in which forthcoming stimuli are processed. Studying this intrinsic-extrinsic interplay is necessary to better understand perceptual integration and selection. Here, we show that this interplay leads to a reconfiguration of functional cortical connectivity that acts as a mechanism to facilitate stimulus processing. Using audiovisual stimulation in anesthetized ferrets, we found that this reconfiguration of coupling modes is context-specific, depending on long-term modulation by repetitive sensory inputs. These reconfigured coupling modes, in turn, lead to changes in latencies and power of local field potential responses that support multisensory integration. Our study demonstrates that this interplay extends across multiple time scales and involves different types of intrinsic coupling. These results suggest a novel large-scale mechanism that facilitates multisensory integration.

neuroscience↗

bioRxiv2018

A computational approach for characterizing the structural basis of intrinsic coupling modes of the cerebral cortex

Intrinsic coupling modes (ICMs) provide a framework for describing the interactions of ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models as well as simple topological ingredients of SC were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are strongly related to SC, except when using ICM measures removing zero-lag synchronizations. Computational models are challenged to predict these ICM patterns consistently, and simple predictions from SC topological features can sometimes outperform them. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs bear a substantial relation to the underlying structural connectivity of the cerebral cortex.

neuroscience↗

bioRxiv2018

Synchrony surfacing: epicortical recording of correlated action potentials

Synchronous spiking of multiple neurons is a key phenomenon in normal brain function and pathologies. Recently, approaches to record spikes from the intact cortical surface using small high-density arrays of microelectrodes have been reported. It remained unaddressed how epicortical spiking relates to intracortical unit activity. We introduce a mesoscale approach using an array of 64 electrodes with intermediate diameter (250 {micro}m) and combined large-coverage epicortical recordings in ferrets with intracortical recordings via laminar probes. Empirical data and modeling strongly suggest that our epicortical electrodes selectively captured synchronized spiking of neurons in the subjacent cortex. As a result, responses to sensory stimulation were more robust and less noisy as compared to intracortical activity, and receptive field properties were well preserved in epicortical recordings. This should promote insights into assembly-coding beyond the informative value of subdural EEG or single-unit spiking, and be advantageous to real-time applications in brain-machine interfacing.\n\nSignificance statementElectrocorticography allows chronic, low-noise recordings from the intact cortical surface - a prerequisite for investigations into brain network dynamics and brain-machine interfaces. Novel electrodes can capture spiking activity at the surface, which should boost precision in the spatial - and time domain, compared to conventional EEG-like measurements. To clarify how surface spiking relates to intracortically fired action potentials, we recorded both types of signal simultaneously from sensory cortices in anesthetized ferrets. Results suggest that mesoscale (250 {micro}m) surface electrodes can selectively capture synchronized spiking from nearby cortical columns, which reduces contamination by non-representative, jittering spikes. Given the high relevance of neural synchrony for sensorimotor and cognitive processing, the novel methodology may improve signal decoding in brain-machine interface approaches.\n\nAuthor contributionsE.G.L., T.B. and A.K.E. conceptualized the research; E.G.L. and F.P. performed experiments; T.B. and E.G.L. wrote Matlab routines for data analysis; T.B. and E.G.L. analyzed the data; T.S. provided technical resources; T.B., E.G.L. and A.K.E. wrote the manuscript; G.E. administrated the project; A.K.E. acquired funding.

neuroscience↗