Biology subjects

Haegens, S.

Publications and source records attributed to Haegens, S..

17 recordsLinked to original sources

bioRxiv2026

Data-driven oscillatory network modeling with condition-dependent coupling laws: Identifying directed neural interactions in working memory attention dynamics

Learning new information in the presence of distracters and changing conditions requires the ability to adapt. In the brain, this adaptive capability has been linked to dynamic interactions between attention and working memory, which enable the selective filtering of irrelevant input while preserving behaviorally relevant information. Specific neural oscillations have been implicated in this process. Here, we introduce a phenomenological data-driven framework for oscillatory network modeling that learns condition-dependent coupling laws directly from neural recordings and enables inference of condition-dependent directed pathways. We apply our approach to magnetoen-cephalography (MEG) data collected while participants performed a working-memory task with and without distracters. Recall dynamics in the non-distracter condition are first modeled using a linear oscillatory network in which each region of interest is represented by two alpha-band harmonic oscillators. We use universal differential equations (UDE), an extension of neural differential equations, to capture distracter-induced changes in coupling laws. Symbolic regression is then used to interpret the modifications identified by UDE as nonlinear functions, and an additional method is proposed to identify the directed pathway from the newly emerging nonlinear terms in the dynamics of brain regions of interest. Despite inter-subject variability, working memory recall data from all four participants examined under distraction showed the emergence of a pathway from the dorsolateral prefrontal cortex (dlPFC) to the primary visual cortex (V1). This finding is consistent with the established role of the dlPFC in cognitive control and suggests that distracter processing recruits a directed interaction from prefrontal to visual regions. More broadly, our results illustrate that combining linear models whose parameters are learned from the data with universal differential equations augmented by interpretability methods enables the identification of condition-dependent coupling laws, their representation as interpretable mathematical functions, and the discovery of candidate directed pathways underlying adaptive changes in oscillatory networks without requiring strong prior assumptions about the underlying mechanisms.

neuroscience↗

bioRxiv2025

Revisiting alpha-theta cross-frequency dynamics during working memory

Prior Electroencephalography (EEG) research has shown that during working memory delay, alpha (8-14 Hz) and theta (4-8 Hz) oscillations tend to form a 2:1 frequency ratio. According to the Binary Hierarchy Brain Body Oscillation Theory (BHBBOT), a recent model grounded in mathematical analysis, such harmonic (2:1) alpha:theta frequency configurations reflect enhanced connectivity between brain regions generating these rhythms. However, this prediction has not yet been empirically tested. In this study, we leveraged Information Theory and the Theory of Weakly Coupled Oscillators (TWCO) to examine whether the previously observed frequency modulations in alpha and theta rhythms during working memory are accompanied by changes in inter-areal connectivity. Contrary to the BHBBOT predictions, both Information Theory metrics and TWCO parameters showed that connectivity between frontal theta and parietal alpha rhythms was significantly reduced during the working-memory delay period (while the proportion of 2:1 ratios increased). In addition, phase locking value, a standard measure of synchrony, was also significantly reduced during working memory delay and was negatively associated with behavioural performance. In conclusion, our results show that the increased occurrence of 2:1 alpha:theta cross-frequency ratios during working memory reflects functional segregation (rather than integration) between frontal and parietal regions.

neuroscience↗

bioRxiv2025

Distinct Alpha Networks Modulate Different Aspects of Perceptual Decision-Making

Why do we sometimes perceive a faint stimulus but miss it at other times? One explanation is that conscious perception fluctuates with the brains internal state, influencing how external stimuli are processed. Ongoing brain oscillations in the alpha band (8-13 Hz), thought to reflect neuronal excitability levels1-5 and play a role in functional inhibition6,7, have been shown as a key contributor to such perceptual variability8,9. Under high alpha conditions, faint stimuli are more likely to be missed8. Some studies suggested alpha oscillations modulate perceptual criterion (c)10-14, shifting the threshold for interpreting sensory information; while others (including our prior work15) suggested alpha modulates sensitivity (d)15-19, changing the precision of sensory encoding. Few studies observed modulations in both metrics, making these results appear mutually exclusive. Most studies have focused solely on overall alpha activity-- whether within a region of interest or across the whole brain--and overlooked the coexistence of multiple distinct alpha networks20-26, which fluctuate in terms of predominance20,27,28 and adapt to behavioural demands29,30. Hence, it remained unclear whether different networks contributions to perception vary with their momentary state. Here, aiming to characterize how different alpha networks influence perceptual decision-making, we analyzed magnetoencephalography (MEG) data recorded while participants performed a visual detection task with threshold-level stimuli. We found that while the visual alpha network modulates perceptual sensitivity, the sensorimotor alpha network modulates criterion in perceptual decision-making. These findings reconcile previous conflicting results and highlight the functional diversity of alpha networks in shaping perception.

neuroscience↗

bioRxiv2024

The association between oscillatory burst features and deviations during human working memory

Oscillatory power across multiple frequency bands has been associated with distinct working memory (WM) processes. Recent research has shown that previous observations based on averaged power are driven by the presence of transient, oscillatory burst-like events, particularly within the alpha, beta, and gamma bands. However, the interplay between different burst events in human WM is not well understood. The current EEG study aimed to investigate the dynamics between alpha (8-12 Hz)/beta (15-29 Hz) and high frequency activity (HFA; 55-80 Hz) bursts in human WM, particularly burst features and error-related deviations during the encoding and maintenance of WM in healthy adults. Oscillatory burst features within the alpha, beta and HFA bands were examined at frontal and parietal electrodes in healthy young adults during a Sternberg working memory task. Averaged power dynamics were driven by oscillatory burst features, most consistently the burst rate and burst power. Alpha/beta and HFA bursts displayed complementary roles in WM processes, in that alpha and beta bursting decreased during encoding and increased during delay, while HFA bursting had the opposite pattern, i.e., increased during encoding and decreased during the delay. Critically, weaker variation in burst dynamics across stages was associated with incorrect responses and impaired overall task performance. Together, these results indicate that successful human WM is dependent on the rise and fall interplay between alpha/beta and HFA bursts, with such burst dynamics reflecting a novel target for the development of treatment in clinical populations with WM deficits.

neuroscience↗

bioRxiv2024

Is there a ubiquitous spectrolaminar motif of local field potential power across primate neocortex?

Mendoza-Halliday, Major et al.1 (referred to as "Mendoza-Halliday et al." for brevity), advocate for a local field potential (LFP)-based approach to functional identification of cortical layers during "laminar" (simultaneous recordings from all cortical layers) multielectrode recordings in nonhuman primates (NHPs). They describe a "ubiquitous spectrolaminar motif" in the primate neocortex: 1) 75-150 Hz power peaks in the supragranular layers, 2) 10-19 Hz power peaks in the infragranular layers and 3) the crossing point of their laminar power gradients identifies Layer 4 (L4). Identification of L4 is critical in general, but especially for Mendoza-Halliday et al. as the "motif" discovery is couched within a framework whose central hypothesis is that gamma activity originates in the supragranular layers and reflects feedforward activity, while alpha-beta activity originates in the infragranular layers and reflects feedback activity. In an impressive scientific effort, Mendoza-Halliday et al. analyzed laminar data from 14 cortical areas in 2 prior macaque studies and compared them to marmoset, mouse, and human data to further bolster the canonical nature of the motif. Identification of such canonical principles of brain operation is clearly a topic of broad scientific interest. Similarly, a reliable online method for L4 identification would be of broad scientific value for the rapidly increasing use of laminar recordings using numerous evolving technologies. Despite Mendoza-Halliday et al.s papers strengths, and its potential for scientific impact, a series of concerns that are fundamental to the analysis and interpretation of laminar activity profile data in general, and local field potential (LFP) signals in particular, led us to question its conclusions. Here, we address four key questions: Q1) Is the spectrolaminar motif ubiquitous, i.e. "found everywhere" or "universal"? Q2) Do features of the motif reliably identify Layer (L) 4? Q3) Are Mendoza-Halliday et al.s newly introduced methods (FLIP and vFLIP) reliable? And Q4) Are the proposed biophysical mechanisms underlying the motif well justified? We used new sets of data comprised of stimulus-evoked laminar response profiles from primary and higher-order auditory cortices (A1 and belt cortex), and primary visual cortex (V1) to test these questions. The rationale for using these areas as a test bed for new methods is that, in contrast to higher-order cortical areas, their laminar anatomy and physiology have already been extensively characterized by prior studies, and there is general agreement across laboratories on key matters like L4 identification. In short, we find that Mendoza-Halliday et al.s findings do not generalize well to these cortical areas. Specifically, regarding Q1: Though we can find a spectrolaminar gradient that is qualitatively consistent with Mendoza-Halliday et al., it is quantifiable in only 61-64% of our recordings, indicating that the motif is common but by no means universal (see "Evaluation of the FLIP method [...]" and "Evaluation of vFLIP [...]"). Regarding Q2: The motifs high/low frequency gradient cross point identified L4 in only 29-33% of our recordings. Regarding Q3: FLIP and vFLIP exhibit marked variability across studies, across brain areas, and spuriously detect cortical layer inversions (see "FLIPs fitting process [...]" and "Evaluation of vFLIP [...]"). Regarding Q4: the biophysical modeling findings cited to support Mendoza-Hallidays conclusions (see "Going forward - in silico [...]") do not reproduce the LFP data trends. While our findings are in many respects at odds with those of Mendoza-Halliday et al., the paper already has, and will continue to spark debate and further experimentation. Hopefully this countervailing presentation will lead to robust collegial efforts to define optimal strategies for applying laminar recording methods in future studies.

neuroscience↗

bioRxiv2024

Common neural mechanisms supporting time judgements in humans and monkeys

There has been an increasing interest in identifying the biological underpinnings of human time perception, for which purpose research in non-human primates (NHP) is common. Although previous work, based on behaviour, suggests that similar mechanisms support time perception across species, the neural correlates of time estimation in humans and NHP have not been directly compared. In this study, we assess whether brain evoked responses during a time categorization task are similar across species. Specifically, we assess putative differences in post-interval evoked potentials as a function of perceived duration in human EEG (N = 24) and local field potential (LFP) and spike recordings in pre-supplementary motor area (pre-SMA) of one monkey. Event-related potentials (ERPs) differed significantly after the presentation of the temporal interval between "short" and "long" perceived durations in both species, even when the objective duration of the stimuli was the same. Interestingly, the polarity of the reported ERPs was reversed for incorrect trials (i.e., the ERP of a "long" stimulus looked like the ERP of a "short" stimulus when a time categorization error was made). Hence, our results show that post-interval potentials reflect the perceived (rather than the objective) duration of the presented time interval in both NHP and humans. In addition, firing rates in monkeys pre-SMA also differed significantly between short and long perceived durations and were reversed in incorrect trials. Together, our results show that common neural mechanisms support time categorization in NHP and humans, thereby suggesting that NHP are a good model for investigating human time perception.

neuroscience↗

bioRxiv2023

Genuine beta bursts in human working memory: controlling for the influence of lower-frequency rhythms

Human working memory is associated with significant modulations in oscillatory brain activity. However, the functional role of brain rhythms at different frequencies is still debated. Modulations in the beta frequency range (15-40 Hz) are especially difficult to interpret because they could be artifactually produced by (more prominent) oscillations in lower frequencies that show non-sinusoidal properties. In this study, we investigate beta oscillations during working memory while controlling for the possible influence of lower frequency rhythms. We collected electroencephalography (EEG) data in 31 participants who performed a spatial working-memory task with two levels of cognitive load. In order to rule out the possibility that observed beta activity was affected by non-sinusoidalities of lower frequency rhythms, we developed an algorithm that detects transient beta oscillations that do not coincide with more prominent lower frequency rhythms in time and space. Using this algorithm, we show that the amplitude and duration of beta bursts decrease with memory load and during memory manipulation, while their peak frequency and rate increase. In addition, interindividual differences in performance were significantly associated with beta burst rates. Together, our results show that beta rhythms are functionally modulated during working memory and that these changes cannot be attributed to lower frequency rhythms with non-sinusoidal properties.

neuroscience↗

bioRxiv2022

Beta band rhythms influence reaction times

Despite their involvement in many cognitive functions, beta oscillations are among the least understood brain rhythms. Reports on whether the functional role of beta is primarily inhibitory or excitatory have been contradictory. Our framework attempts to reconcile these findings and proposes that several beta rhythms co-exist at different frequencies. Beta frequency shifts and their potential influence on behavior have thus far received little attention. In this magnetoencephalography experiment, we asked whether changes in beta power or frequency in auditory cortex and motor cortex influence behavior (reaction times) during an auditory sweep discrimination task. We found that in motor cortex, increased beta power slowed down responses, while in auditory cortex, increased beta frequency slowed down responses. We further characterized beta as transient burst events with distinct spectro-temporal profiles influencing reaction times. Finally, we found that increased motor-to-auditory beta connectivity also slowed down responses. In sum, beta power, frequency, bursting properties, cortical focus, and connectivity profile all influenced behavioral outcomes. Our results imply that the study of beta oscillations requires caution as beta dynamics are multifaceted phenomena, and that several dynamics must be taken into account to reconcile mixed findings in the literature.

neuroscience↗

bioRxiv2022

Distinct beta frequencies reflect categorical decisions

Beta oscillations are involved in a variety of cognitive functions beyond their traditional sensorimotor role. Based on prior findings of content-specific beta synchronization during working memory and decision making, we hypothesized that beta activity supports the activation and reactivation of cortical representations by mediating neural ensemble formation within and between brain regions. We here found that beta activity in monkey dorsolateral prefrontal cortex (dlPFC) and in pre-supplementary motor area (preSMA) reflects the content of a stimulus in relation to the task context, regardless of its objective properties. In multiple versions of a categorization task, we changed the boundary between categories from one block of trials to the next, such that a stimulus which belonged to one of two categories during one block could belong to the other category during the next one. During a delay in which monkeys had to hold their categorical decision in mind, we found that two distinct beta-band frequencies were consistently associated with the same two relative categories, and that activity in these respective bands predicted the animals responses. We characterized beta at these frequencies as transient bursts with distinct temporal profiles. We further showed that dlPFC and preSMA are connected via these distinct frequency channels, with dlPFC driving the frequency separation, a result supported by Granger causality and spike-field coherence analyses. In sum, these results provide support for the role of beta in forming neural ensembles, and further show that such ensembles synchronize at different beta frequencies.

neuroscience↗

bioRxiv2022

Naturalistic language comprehension is supported by alpha and beta oscillations linked to domain-general inhibition and reactivation

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. Alpha oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while beta oscillations are linked to the reactivation of content representations. Can the proposed functional role of alpha and beta oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language processing. Twenty-two (18 female) Dutch native speakers listened to stories in spoken Dutch and French while magnetoencephalography (MEG) was recorded. We used dependency parsing to identify three dependency states at each word, as the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed linear forward models to predict alpha and beta power from the dependency features. Results showed that dependency features predict alpha and beta power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in the alpha band, while frontal and parietal, higher-order language regions, and motor regions are mostly involved in the beta band. Critically, alpha and beta band dynamics seem to subserve language comprehension tapping into syntactic structure building and semantic composition by providing low-level mechanistic operations for inhibition and reactivation processes. Overall, this study sheds light on the role of alpha and beta oscillations during naturalistic language processing, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes. Significance StatementPrior research identified the functional role of alpha and beta oscillations in basic perceptual and motor functions. However, it remains unclear whether their proposed role can be generalized to higher-level processes during language comprehension. Here, we found that high-level syntactic features predict alpha and beta power in language-related regions beyond low-level linguistic features when listening to comprehensible naturalistic speech. Our work contributes to the debate about whether the functional roles of brain oscillations are domain-general or depend on the task at hand. We offer experimental findings that integrate a neuroscientific framework on the role of brain oscillations as "building blocks" with language comprehension as a compositional process, and novel evidence regarding the encoding of higher-level syntactic operations in the brain. This supports the view of a domain-general role of cortical oscillations across the hierarchy of cognitive functions, from low-level sensory operations to complex linguistic processes.

neuroscience↗

bioRxiv2022

Visual working memory recruits two functionally distinct alpha rhythms in posterior cortex

Oscillatory activity in the human brain is dominated by posterior alpha oscillations (8-14 Hz), which have been shown to be functionally relevant in a wide variety of cognitive tasks. Although posterior alpha oscillations are commonly considered a single oscillator anchored at an individual alpha frequency (IAF; [~]10 Hz), previous work suggests that IAF reflects a spatial mixture of different brain rhythms. In this study, we assess whether Independent Component Analysis (ICA) can disentangle functionally distinct posterior alpha rhythms in the context of visual short-term memory retention. Magnetoencephalography (MEG) was recorded in 33 subjects while performing a visual working memory task. Group analysis at sensor level suggested the existence of a single posterior alpha oscillator that increases in power and decreases in frequency during memory retention. Conversely, single-subject analysis of independent components revealed the existence of two dissociable alpha rhythms: one that increases in power during memory retention (Alpha1) and another one that decreases in power (Alpha2). Alpha1 and Alpha2 rhythms were differentially modulated by the presence of visual distractors (Alpha1 increased in power while Alpha2 decreased) and had an opposite relationship with accuracy (positive for Alpha1 and negative for Alpha2). In addition, Alpha1 rhythms showed a lower peak frequency, a narrower peak width, a greater relative peak amplitude and a more central source than Alpha2 rhythms. Together, our results demonstrate that modulations in posterior alpha oscillations during short-term memory retention reflect the dynamics of at least two distinct brain rhythms with different functions and spatiospectral characteristics. Significance statementAlpha oscillations are the most prominent feature of the human brains electrical activity, and consist of rhythmic neuronal activity in posterior parts of the cortex. Alpha is usually considered a single brain rhythm that changes in power and frequency to support cognitive operations. We here show that posterior alpha entails at least two dissociable rhythms with distinct functions and characteristics. These findings could solve previous inconsistencies in the literature regarding the direction of task-related alpha power/frequency modulations and their relation to cognitive performance. In addition, the existence of two distinct posterior alpha rhythms could have important consequences for the design of neurostimulation protocols aimed at modulating alpha oscillations and subsequently cognition.

neuroscience↗

bioRxiv2021

The impact of eye closure on anticipatory alpha activity in a tactile discrimination task

One of the very first observations made regarding alpha oscillations (8-14 Hz), is that they increase in power over posterior areas when awake participants close their eyes. Recent work, especially in the context of (spatial) attention, suggests that alpha activity reflects a mechanism of functional inhibition. However, it remains unclear how eye closure impacts anticipatory alpha modulation observed in attention paradigms, and how this affects subsequent behavioral performance. Here, we recorded magnetoencephalography (MEG) in 33 human participants performing a tactile discrimination task with their eyes open vs. closed. We replicated the hallmarks of previous somatosensory spatial attention studies: alpha lateralization across the somatosensory cortices as well as alpha increase over posterior regions. Furthermore, we found that eye closure leads to (i) reduced task performance, (ii) widespread increase in alpha power, and (iii) reduced anticipatory visual alpha modulation (iv) with no effect on somatosensory alpha lateralization. Regardless of whether participants had their eyes open or closed, increased posterior alpha power and somatosensory alpha lateralization improved their performance. Thus, we provide evidence that eye closure does not alter the impact of anticipatory alpha modulations on behavioral performance. We propose there is an optimal posterior alpha level for somatosensory task performance, which can be achieved through a combination of eye closure and top-down anticipatory attention. Significance StatementAlpha oscillations are dominant when awake participants have their eyes closed. Furthermore, alpha is known to modulate with anticipatory attention, and has been ascribed a role of active functional inhibition. Surprisingly, the link between anticipatory alpha and eye closure remains unclear. Here we collected MEG data while human participants performed a tactile discrimination task either with their eyes open or closed. Eye closure led to a widespread increase in alpha power, and affected anticipatory visual alpha modulation but not somatosensory alpha lateralization. Importantly, eye closure did not affect the correlation between alpha and task performance. Our findings provide novel insights into how eye closure impacts anticipatory alpha modulation, and how optimal alpha levels for task performance can be achieved differently.

animal behavior and cognition↗

bioRxiv2021

Shaping information processing: the role of oscillatory dynamics in a working-memory task

Neural oscillations are thought to reflect low-level operations that can be employed for higher-level cognitive functions. Here, we investigated the role of brain rhythms in the 1-30 Hz range by recording MEG in human participants performing a visual delayed match-to-sample paradigm in which orientation or spatial frequency of sample and probe gratings had to be matched. A cue occurring before or after sample presentation indicated the to-be-matched feature. We demonstrate that alpha/beta power decrease tracks the presentation of the informative cue and indexes faster responses. Moreover, these faster responses coincided with an augmented phase alignment of slow oscillations, as well as phase-amplitude coupling between slow and fast oscillations. Importantly, stimulus decodability was boosted by both low alpha power and high beta power. In summary, we provide support for a comprehensive framework in which different rhythms play specific roles: slow rhythms control input sampling, while alpha (and beta) gates the information flow, beta recruits task-relevant circuits, and the timing of faster oscillations is controlled by slower ones. Significance statementBrain oscillations reflect low-level operations, building blocks, that control the flow of information through the brain. We propose and test a novel comprehensive framework in which slow oscillations control input sampling, alpha gates information flow, beta recruits task-relevant circuits, and the timing of faster oscillations is controlled by slower ones. We collected MEG data while participants performed a visual delayed match-to-sample task with pre- & retro-cues. Phase alignment of slow oscillations, governing input sampling, indexed faster responses. Alpha/beta power, gating information flow, boosted behavior & tracked informative cues. Low alpha (gating) & high beta (circuit-setup) power boosted signal information content. This is an essential step towards a more unified framework regarding the role of oscillatory dynamics in shaping information processing.

neuroscience↗

bioRxiv2021

Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Spontaneous fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on invasive electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

neuroscience↗

bioRxiv2021

Alpha oscillations shape sensory representation and perceptual accuracy

Alpha activity (8-14 Hz) is the dominant rhythm in the awake brain, and thought to play an important role in setting the brains internal state. Previous work has associated states of decreased alpha power with enhanced neural excitability. However, evidence is mixed on whether and how such excitability enhancement modulates sensory signals of interest versus noise differently, and what, if any, the consequences are for subsequent perception. Here, human subjects (male and female) performed a visual detection task in which we manipulated their decision criteria in a block-wise manner. While our manipulation led to substantial criterion shifts, these shifts were not reflected in pre-stimulus alpha-band changes. Rather, lower pre-stimulus alpha power in occipital-parietal areas improved perceptual sensitivity and enhanced information content decodable from neural activity patterns. Additionally, oscillatory alpha phase immediately before stimulus presentation modulated accuracy. Together, our results suggest that alpha-band dynamics modulate sensory signals of interest more strongly than noise. Significance statementThe internal state of our brain fluctuates, giving rise to variability in perception and action. Neural oscillations, most prominently in the alpha-band, have been suggested to play a role in setting this internal state. Here, we show that ongoing alpha-band activity in occipital-parietal regions predicts the quality of visual information decodable in neural activity patterns, and subsequently human observers sensitivity in a visual detection task. Our results provide comprehensive evidence that visual representation is modulated by ongoing alpha-band activity, and advance our understanding on how, when faced with unchanging external stimuli, internal neural fluctuations influence perception and behavior.

neuroscience↗

bioRxiv2020

No behavioral evidence for rhythmic facilitation of perceptual discrimination

It has been hypothesized that internal oscillations can synchronize (i.e., entrain) to external environmental rhythms, thereby facilitating perception and behavior. To date, evidence for the link between the phase of neural oscillations and behavior has been scarce and contradictory; moreover, it remains an open question whether the brain can use this tentative mechanism for active temporal prediction. In our present study, we conducted a series of auditory pitch discrimination tasks with 181 healthy participants in an effort to shed light on the proposed behavioral benefits of rhythmic cueing and entrainment. In the three versions of our task, we observed no perceptual benefit of purported entrainment: targets occurring in-phase with a rhythmic cue provided no perceptual benefits in terms of discrimination accuracy or reaction time when compared with targets occurring out-of-phase or targets occurring randomly, nor did we find performance differences for targets preceded by rhythmic vs. random cues. However, we found a surprising effect of cueing frequency on reaction time, in which participants showed faster responses to cue rhythms presented at higher frequencies. We therefore provide no evidence of entrainment, but instead a tentative effect of covert active sensing in which a faster external rhythm leads to a faster communication rate between motor and sensory cortices, allowing for sensory inputs to be sampled earlier in time.

neuroscience↗

bioRxiv2019

Dissociation of broadband high-frequency activity and neuronal firing in the neocortex

Broadband High-frequency Activity (BHA; 70-150 Hz), also known as \"high gamma,\" a key analytic signal in human intracranial recordings is often assumed to reflect local neural firing (multiunit activity; MUA). Accordingly, BHA has been used to study neuronal population responses in auditory (1,2), visual (3,4), language (5), mnemonic processes (6-9) and cognitive control (10,11). BHA is arguably the electrophysiological measure best correlated with the Blood Oxygenation Level Dependent (BOLD) signal in fMRI (12-13). However, beyond the fact that BHA correlates with neuronal spiking (12, 14-16), the neuronal populations and physiological processes generating BHA are not precisely defined. Although critical for interpreting intracranial signals in human and non-human primates, the precise physiology of BHA remains unknown. Here, we show that BHA dissociates from MUA in primary visual and auditory cortex. Using laminar multielectrode data in monkeys, we found a bimodal distribution of stimulus-evoked BHA across depth of a cortical column: an early-deep, followed by a later-superficial layer response. Only, the early-deep layer BHA had a clear local MUA correlate, while the more prominent superficial layer BHA had a weak or undetectable MUA correlate. In many cases, particularly in V1 (70%), supragranular sites showed strong BHA in lieu of any detectable increase in MUA. Due to volume conduction, BHA from both the early-deep and the later-supragranular generators contribute to the field potential at the pial surface, though the contribution may be weighted towards the late-supragranular BHA. Our results demonstrate that the strongest generators of BHA are in the superficial cortical layers and show that the origins of BHA include a mixture of the neuronal action potential firing and dendritic processes separable from this firing. It is likely that the typically-recorded BHA signal emphasizes the latter processes to a greater extent than previously recognized.

neuroscience↗