Biology subjects

Helfrich, R. F.

Publications and source records attributed to Helfrich, R. F..

10 recordsLinked to original sources

bioRxiv2026

An inhibitory circuit motif governs oscillation-dependent coupling between aperiodic activity and neural spiking

Behavior arises from coordinated neural population activity, yet how spiking and synaptic interactions give rise to extracellular population signals, including local field potentials (LFPs), remains unresolved. Beyond oscillations, aperiodic LFP activity has emerged as a putative marker of neural excitability, but its neurophysiological basis and relationship to neural spiking are unclear. Here we employed optogenetics and simultaneous single-unit and LFP recordings in mouse visual cortex to quantify how spiking relates to oscillatory and aperiodic dynamics across cortical states and behavioral contexts. To test circuit mechanisms, we optogenetically suppressed the activity of somatostatin (SST), vasoactive intestinal peptide (VIP), or parvalbumin (PV) interneurons to causally manipulate inhibitory drive, thereby dissociating spiking, aperiodic activity, and gamma oscillations. Across conditions, aperiodic activity tracked neural spiking in a manner consistent with computational predictions, but this coupling was strongly context- and state-dependent: high oscillatory synchrony attenuated the relationship between aperiodic activity and spiking. These results demonstrate that state-dependent changes in neural excitability shift circuit activity between oscillation- and aperiodic-dominated regimes, placing principled limits on interpreting neural mass signals at synaptic or cellular scales.

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bioRxiv2025

Sensory and action neural tuning explains how priors guide human visual decisions

Prior expectations bias how we perceive the world. Despite well-characterized behavioral effects of priors, such as confirmation bias, their neural mechanisms remain unclear. Contemporary theories postulate conflicting predictions: does the brain enhance expected sensory information (sharpening the expected representation) or rather prioritize unexpected information (dampening the expected representations)? Here, we combined reversal learning with a noisy motion discrimination task to investigate how priors impact sensory and action information processing. Using behavioral modeling to infer participants latent priors and EEG to track neural dynamics, we demonstrated that priors differentially impact sensory and action representations over time. While priors introduced long-lasting biases on action coding irrespective of their validity, sensory information was selectively enhanced with confirmatory evidence. Critically, dampening of action representations predicted confirmation biases, whereas sensory tuning dynamics tracked speed-accuracy trade-offs. These findings reveal a dissociable and temporally dynamic influence of priors in visual decisions, reconciling competing theories of predictive perception. Significance statementPrior expectations, abstract rules, and recent decisions impact perception and ensuing actions. While priors are beneficial in most circumstances, they might be detrimental in other scenarios, as exemplified by confirmation biases, serial response biases, or switch costs. Albeit well-characterized at the behavioral level, the neural mechanisms underlying these biases remain undetermined. By tracking participants latent priors and neural dynamics with high-density EEG, the authors demonstrate that priors differentially impact sensory and action information, uncovering the neural mechanisms underlying confirmation biases and speed-accuracy trade-offs in predictive perception.

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bioRxiv2025

Hexagonal modulation of theta rhythmic attentional sampling of visual space

Spatial attention improves visual perception by selecting behaviorally relevant sensory signals. Traditionally, attention has been conceptualized as a static spotlight, while recent evidence posited that attention operates as a moving spotlight that samples visual space sequentially in discrete snapshots that are clocked by theta rhythms ([~]3-8 Hz). While theta rhythmic attentional sampling has mainly been observed in fronto-parietal and occipital areas, theta oscillations also hallmark entorhinal-hippocampal grid-cell networks, which encode physical space in hexagonal patterns that guide overt exploration and navigation. We hypothesized that visual attention might rely on the same underlying principles and sample visual space in a hexagonal, grid-like configuration. To test this hypothesis, twenty participants performed a cue-guided attention task that probed behavioral performance as a function of space and time. Reaction times were assessed as a function of spatial location and varying cue-target intervals, which revealed prominent, spatially-structured theta rhythms. Specifically, higher theta power was evident at spatial locations that were aligned to multiples of 60{degrees}, consistent with an underlying hexagonal organization. Participants that exhibited stronger hexagonal sampling relied less on the spatial cue to guide their attentional allocation. In sum, these findings suggest that covert visual attention relies on an underlying hexagonal grid-like structure known from the entorhinal-hippocampal system and highlight that theta rhythms reflect a common organizing principle for spatial cognition. Significance StatementAttention prioritizes sensory inputs to optimize behavior. But how does attention sample the environment in space and time? Here, we demonstrate that attentional sampling of visual space is not uniform, but preferentially explores locations that are oriented along a hexagonal pattern, reminiscent of the spatial configuration of entorhinal-hippocampal grid cells. Moreover, covert attentional sampling was clocked by theta oscillations (3-8 Hz). In sum, these findings provide evidence for a shared neural basis of underlying spatial attention and navigation and reveal that theta rhythms orchestrate sampling behaviors in space and time as a unifying principle underlying spatial cognition.

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bioRxiv2024

Attentional Information Routing in The Human Brain

Brain-wide communication supporting flexible behavior requires coordination between sensory and associative regions but how brain networks route sensory information at fast timescales to guide action remains unclear. Using human intracranial electrophysiology and spiking neural networks during spatial attention tasks, where participants detected targets at cued locations, we show that high-frequency activity bursts (HFAb) mark temporal windows of elevated population firing that enable fast, long-range communications. HFAbs were evoked by sensory cues and targets, dynamically coupled to low-frequency rhythms. Notably, both the strength of cue-evoked HFAbs and their decoupling from slow rhythms predicted behavioral accuracy. HFAbs synchronized across the brain, revealing distinct cue- and target-activated subnetworks. These subnetworks exhibited lead-lag dynamics following target onset, with cue-activated subnetworks preceding target-activated subnetworks when cues were informative. Computational modeling suggested that HFAbs reflect transitions to population spiking, denoting temporal windows for network communications supporting attentional performance. These findings establish HFAbs as signatures of population state transitions, supporting information routing across distributed brain networks.

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bioRxiv2022

Periodic neglect after frontoparietal lesions provides causal evidence for rhythmic attention sampling

Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time even in states of presumed sustained attention. Recent evidence suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results uncovered that frontoparietal lesions introduce periodic neglect, i.e., temporally-specific behavioral deficits that were aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with healthy controls during optimal phases but attenuated during the less excitable sub-cycles. Theta-dependent sampling (3 - 8 Hz) was causally dependent on prefrontal cortex, while alpha-band sampling (8 - 14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high amplitude, low frequency brain activity is not epiphenomenal, but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.

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bioRxiv2022

An evolutionary conserved division-of-laborbetween hippocampal and neocortical sharp-wave ripplesorganizes information transfer during sleep

The hippocampal sharp-wave ripple (SW-R) is the key substrate of the hippocampal-neocortical dialogue underlying memory formation. Recently, it became evident that SW-R are not unique to archicortex, but constitute a wide-spread neocortical phenomenon. To date, little is known about morphological and functional similarities between archi- and neocortical SW-R. Leveraging intracranial recordings from the human hippocampus and prefrontal cortex during sleep, our results reveal region-specific functional specializations, albeit a near-uniform morphology. While hippocampal SW-R trigger directional hippocampal-to-neocortical information flow, neocortical SW-R reduce information flow to minimize interference. At the population level, hippocampal SW-R confined population dynamics to a low-dimensional subspace, while neocortical SW-R diversified the population response; functionally uncoupling the hippocampal-neocortical network. Critically, our replication in rodents demonstrated the same division-of-labor between archi-and neocortical SW-R. These results uncover an evolutionary preserved mechanism where coordinated interplay between hippocampal and neocortical SW-R temporally segregates hippocampal information transfer from neocortical processing.

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bioRxiv2022

Human REM sleep controls neural excitability in support of memory formation

Sleep oscillations provide a key substrate to facilitate memory processing, the underlying mechanism of which may involve the overnight homeostatic regulation of plasticity at a synaptic and whole-network level. However, there remains a lack of human data demonstrating if and how sleep enhances memory consolidation and associated neural homeostasis. We combined intracranial recordings and scalp electroencephalography (EEG) in humans to reveal a new role for rapid eye movement (REM) sleep in promoting the homeostatic recalibration of optimal excitation/inhibition-balance. Moreover, the extent of this REM-sleep homeostatic recalibration predicted the success of overnight memory consolidation, expressly the modulation of hippocampal-- neocortical excitability favoring remembering rather than forgetting. The findings describe a novel, fundamental role of human REM sleep in maintaining neural homeostasis, thereby enhancing long-term memory.

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bioRxiv2021

Slow oscillation-spindle coupling strength predicts real-life gross-motor learning in adolescents and adults

Previously, we demonstrated that precise temporal coordination between slow oscillations (SO) and sleep spindles indexes declarative memory network development (Hahn et al., 2020). However, it is unclear whether these findings in the declarative memory domain also apply in the motor memory domain. Here, we compared adolescents and adults learning juggling, a real-life gross-motor task. We found that improved task proficiency after sleep lead to an attenuation of the learning curve, suggesting a dynamic juggling learning process. We employed individualized cross-frequency coupling analyses to reduce inter and intra-group variability of oscillatory features. Advancing our previous findings, we identified a more precise SO-spindle coupling in adults compared to adolescents. Importantly, coupling precision over motor areas predicted overnight changes in task proficiency and learning curve, indicating that SO-spindle coupling is sensitive to the dynamic motor learning process. Our results provide first evidence that regionally specific precisely coupled sleep oscillations support gross-motor learning.

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bioRxiv2020

Slow wave-spindle coupling during sleep predicts language learning and associated oscillatory activity

Sentence comprehension involves the rapid decoding of both semantic and grammatical information, a process fundamental to communication. As with other complex cognitive processes, language comprehension relies, in part, on long-term memory. However, the electrophysiological mechanisms underpinning the initial encoding and generalisation of higher-order linguistic knowledge remain elusive, particularly from a sleep-based consolidation perspective. One candidate mechanism that may support the consolidation of higher-order language is the temporal coordination of slow oscillations (SO) and sleep spindles during non-rapid eye movement sleep (NREM). To examine this hypothesis, we analysed electroencephalographic (EEG) data recorded from 35 participants (Mage = 25.4, SD = 7.10; 16 males) during an artificial language learning task, contrasting performance between individuals who were given an 8hr nocturnal sleep period or an equivalent period of wake. We found that sleep relative to wake was associated with superior performance for rules that followed a sequence-based word order. Post-sleep sequence-based word order processing was further associated with less task-related theta desynchronisation, an electrophysiological signature of successful memory consolidation, as well as cognitive control and working memory. Frontal NREM SO-spindle coupling was also positively associated with behavioural sensitivity to sequence-based word order rules, as well as with task-related theta power. As such, theta activity during retrieval of previously learned information correlates with SO-spindle coupling, thus linking neural activity in the sleeping and waking brain. Taken together, this study presents converging behavioral and neurophysiological evidence for a role of NREM SO-spindle coupling and task-related theta activity as signatures of successful memory consolidation and retrieval in the context of higher-order language learning. SIGNIFICANCE STATEMENTThe endogenous temporal coordination of neural oscillations supports information processing during both wake and sleep states. Here we demonstrate that slow oscillation-spindle coupling during non-rapid eye movement sleep predicts the consolidation of complex grammatical rules and modulates task-related oscillatory dynamics previously implicated in sentence processing. We show that increases in theta power predict enhanced sensitivity to grammatical violations after a period of sleep and strong slow oscillation-spindle coupling modulates subsequent task-related theta activity to influence behaviour. Our findings reveal a complex interaction between both wake- and sleep-related oscillatory dynamics during the early stages of language learning beyond the single word level.

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bioRxiv2019

An Electrophysiological Marker of Arousal Level in Humans

Deep non-rapid eye movement sleep (NREM) - also called slow wave sleep (SWS) - and general anesthesia are prominent states of reduced arousal linked to the occurrence of slow oscillations in the electroencephalogram (EEG). Rapid eye movement (REM) sleep, however, is also associated with a diminished arousal level, but is characterized by a desynchronized, wake-like EEG. This observation challenges the notion of oscillations as the main physiological mediator of reduced arousal. Using intracranial and surface EEG recordings in four independent data sets, we establish the 1/f spectral slope as an electrophysiological marker that accurately delineates wakefulness from anesthesia, SWS and REM sleep. The spectral slope reflects the non-oscillatory, scale-free measure of neural activity and has been proposed to index the local balance between excitation and inhibition. Taken together, these findings reconcile the long-standing paradox of reduced arousal in both REM and NREM sleep and provide a common unifying physiological principle -- a shift in local Excitation/ Inhibition balance -- to explain states of reduced arousal such as sleep and anesthesia in humans.\n\nSignificance StatementThe clinical assessment of arousal levels in humans depends on subjective measures such as responsiveness to verbal commands. While non-rapid eye movement (NREM) sleep and general anesthesia share some electrophysiological markers, rapid eye movement sleep (REM) is characterized by a wake-like electroencephalogram. Here, we demonstrate that non-oscillatory, scale-free electrical brain activity -- recorded from both scalp electroencephalogram and intracranial recordings in humans -- reliably tracks arousal levels during both NREM and REM sleep as well as under general anesthesia with propofol. Our findings suggest that non-oscillatory brain activity can be used effectively to monitor vigilance states.

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