Progress in Neurobiology

Beta-band activity (13-30 Hz) is a hallmark of human movement, yet a unifying account of its functional role remains unresolved. Although typically described as a sustained oscillation, beta activity is increasingly recognised to consist of transient bursts. More recently, beta bursts have been shown to exhibit heterogeneous waveforms. Here, we ask whether variability in burst shape corresponds to separable computational roles during motor adaptation. Using high-density MEG, we recorded neural activity while participants performed a visuomotor rotation task under either implicit (sensorimotor adaptation) or explicit (strategic re-aiming) learning conditions. Conventional metrics, beta power and burst rate, showed context-dependent modulation during preparation but provided limited insight into trial-by-trial behaviour. In contrast, sorting bursts according to their waveforms revealed a repertoire of burst types with dissociable temporal dynamics and context-dependent modulation. Crucially, during post-movement evaluation, distinct burst subtypes showed opposing and temporally specific relationships with behavioural error: one subtype decreased with increasing error, whereas others increased. Together, these findings indicate that beta activity comprises separable transient events with specific computational roles, and that accounting for waveform diversity is essential for understanding how cortical beta supports adaptive behaviour.

The transformation of sensory information into goal-directed motor plans and actions is known to emerge from coordinated activity between parietal and motor areas. Within this network, anticipation plays a critical role, enabling the brain to predict upcoming sensory inputs and prepare appropriate actions before sensory information becomes available. However, it remains unclear whether fronto-parietal interactions during motor anticipation follow a serial hierarchical organization or reflect distributed and reciprocal processing. To address this open question, we trained two rhesus macaques to perform a visually-guided sequential reaching task, in which the predictability of target location increased within the sequence. Analysis of eye and hand movements revealed that the degree of movement anticipation increased with target predictability. The direction of the upcoming reach toward predictable targets could be decoded from preparatory neural activity prior to target onset in both dorsal premotor-primary motor cortex (PMd/M1) and parietal area 7A. Using feature-specific information transfer analysis, we found that information about the upcoming movement direction was transmitted between 7A and PMd/M1 through bidirectional, yet asymmetric, interactions. Contrary to classical hierarchical models predicting serial activation across parietal and motor areas, parietal-to-motor interactions did not occur earlier than motor-to-parietal interactions. Instead, our findings support a heterarchical and reciprocal fronto-parietal network in which anticipatory processes adjust the timing of preparatory activity to facilitate eye-hand coordination during reaches to predictable targets.

Path integration and spatial updating refer to the integration of self-motion information during navigation to update ones start location and the positions of other locations, respectively. Even though path integration has been described as a fundamental process whose output may serve as a building block for other navigational computations like spatial updating, the exact relationship between path integration and spatial updating is unknown. Here we addressed this question with an eye-tracking behavioral experiment and a subsequent fMRI study. Despite experiencing identical self-motion cues, participants showed differential eye fixation patterns and responded more quickly during spatial updating than during path integration, casting doubt on the fundamental role of path integration. Neuroimaging results showed that the precuneus and the dorsal premotor cortex were more activated during spatial updating, but the precuneus had stronger functional connectivity with the thalamus and the frontal cortex during path integration. Further supporting this dissociation, the two tasks invoked distinct brain-wide inter-regional functional networks. Together, the combined findings of both experiments suggest that spatial updating and path integration are dissociable navigation processes supported by distinct behavioral and neural mechanisms, rather than one process operating on the basis of the other.

Value-based decision-making is a dynamic and idiosyncratic process which requires appraising the value of options and comparing the values to select the best choice. An emerging view of orbitofrontal cortex (OFC) is that it achieves this by representing values serially during deliberation, alternating back-and-forth between transient states that encode the value of different options. While the time spent in each value state is known to reflect choice behavior, the source of the alternating dynamics remains unclear. One possibility is that fluctuations in value may be driven by attentional shifts between the choice options. Conversely, value dynamics in OFC may be generated locally, enabling OFC value signals to influence decision-making independently from attention. To test these hypotheses, we recorded from OFC and lateral prefrontal cortex (LPFC), a major attentional area in prefrontal cortex, to determine whether their population-level activity correlated in a manner consistent with crosstalk between neuronal systems involved in value and spatial attention. We found that OFC and LPFC selectively encoded option values and spatial locations, respectively, reflecting their specialized roles in cognition. Despite this functional dissociation, both OFC and LPFC dynamics were strongly affected by overt attention: which caused the value and spatial location of the fixated option to be represented at the same time. Additionally, fluctuations in the encoding strength of value in OFC and space in LPFC were temporally correlated above and beyond the effect of gaze, reflecting the effect of covert attention.

Despite numerous investigations, a comprehensive electrophysiological characterization of iconic memory remains lacking. Through a partial report paradigm, we aimed to shed light on this topic by disentangling electrophysiological activity related to stimulus perception from that linked with the specific task. We collected EEG data from 26 participants while they performed a partial report task. They were shown circular arrays of six letters lasting 100 ms. After the stimulus, an acoustic cue instructed the participant to report on which side of the array. Differences between reporting conditions were primarily evident in the time window 850-1100 ms, characterized by a positive component predominantly over parieto-occipital electrodes ipsilateral to the reporting side. Through linear regression, we also found a positive relationship between P1 and participants accuracy, as well as negative relationships between P3, VCR, TIF, and accuracy. Our results provide an overview of the different processes involved in iconic memory, corroborating the distinction between a series of neural mechanisms responsible for encoding and maintaining the entire stimulus and higher-order processes in charge of selecting an information subset for conscious report. The TIF component, in particular, could act as a key filtering mechanism to prevent irrelevant information from being selected for further processing. Our results provide, for the first time, a thorough characterization of the electrophysiological dynamics behind iconic memory. Moreover, implications for the consciousness debate are discussed, particularly regarding the overflow argument and how our results could be read through its lens.

Human attention is inherently transient and limited in span to only a few moments without lapsing. The intrinsic dynamics of large-scale neurocognitive networks are thought to contribute to these lapses and result in the unavoidable fluctuations in attention that constrain its span. However, it remains unclear how the millisecond temporal dynamics of specific electrophysiological brain states contribute to the endogenous maintenance of attention or the onset of attentional lapses. In the present study, we investigated whether the strength and millisecond dynamics of brain electric microstates differentiate states of focus from inattention and contribute to the endogenous maintenance of attention over short and long timescales. We recorded 128-channel EEG while participants maintained their attention during the wait time delay of trials in the Sustained Attention to Cue Task (SACT) and segmented the EEG into a categorized time series of microstates based on data-driven clustering of topographic voltage patterns. The findings revealed that the prevalence and rate of occurrence of microstates C and E in the wait time delay of trials differentiated trials in which the target stimulus was correctly detected from incorrectly detected. These same microstates were also implicated in the maintenance of attention over short and long timescales, with their time-varying dynamics changing systematically during the wait time delay of trials and over the course of the task session. Together, these findings demonstrate the sensitivity of microstates to variation in attentional states and suggest that the millisecond dynamics of these brain states contribute to the maintenance of attention over time.

Efficient metabolic waste clearance, via the postulated glymphatic system, is essential for neural homeostasis. However, direct visualization of tissue-cerebrospinal fluid (CSF) exchange remains limited, leading to ongoing debate in the neuroscientific field. The present work revealed evidence of tissue-CSF water exchange in the live human cortex, by employing a novel MRI technique demonstrating the flux of water molecules across the perivascular interface. We observed robust water exchange inside the cortical ribbon, which was more prominent than white matter and deep brain tissue. We validated that the signal originates from CSF and is independent of cerebral perfusion. Water exchange between tissue and CSF declined with age. Furthermore, we demonstrated for the first time that tissue-CSF exchange was impaired in Alzheimers disease (AD), in particular in regions where the perivascular space is clogged by anti-amyloid immunotherapy.

Working memory (WM) enables us to maintain and manipulate information over time, but how the brain organizes sequential information locally and across networks remains unclear. Recent work suggests that slow and fast theta oscillations serve different roles in memory, yet their distinct contributions to sequential WM are unknown. Based on evidence that the hippocampus (HC) and orbitofrontal cortex (OFC) support sequential WM and that slower theta cycles provide optimal temporal windows for organizing items in WM, we predicted that these regions would coordinate via slow theta dynamics. We analyzed intracranial EEG from the HC, OFC, and amygdala (AMY) in 21 neurosurgical patients (7 female, 13-54 years of age; M {+/-} SD, 30 {+/-} 11.2 years) performing a delayed match-to-sample WM task. We assessed phase locking between regions, phase-amplitude coupling within regions, and neuronal phase coding for slow (~1-4.5 Hz) and fast (~4.5-8 Hz) theta oscillations. We found significant slow and fast theta synchrony between all regions, but identical anatomical pathways produced opposing behavioral effects depending on oscillatory frequency, particularly during higher cognitive demand. Slow theta synchrony was associated with faster response times (RTs), while fast theta synchrony between HC and OFC hindered both accuracy and RTs. Unexpectedly, AMY modulated RT through demand-dependent slow theta synchrony, where AMY-OFC synchrony predicted faster RTs during maintenance and HC-AMY synchrony predicted faster RTs during higher cognitive demand. Sustained coupling between slow theta oscillations and high-frequency broadband activity within each region suggests that local organization coincides with beneficial network behavioral effects. These results establish a frequency-opponent mechanism in which theta oscillation frequencies determine whether HC-OFC circuits facilitate or impair sequential WM.

The prefrontal cortex (PFC) plays a critical role in maintaining working memory (WM) representations while filtering irrelevant distractors. In macaques, PFC neurons exhibit persistent delay period activity that is robust to distractor interference. The common marmoset has emerged recently as a complementary primate model for investigating the neural basis of cognitive processes including WM, in part because the relatively lissencephalic cortex of this species enables laminar recordings which could provide substantial insight into the microcircuit basis of these functions. It remains unknown however, whether marmoset WM performance is robust to distractors presented during delay periods of WM tasks, and how such distractor filtering may be implemented in PFC circuits. Here, we addressed this gap by conducting wireless recordings of PFC in freely moving marmosets performing a touchscreen-based delayed-match-to-location (DML) task in which a salient visual distractor was presented during the delay period on a subset of trials. Marmosets maintained WM performance on distractor trials, showing a decrease in accuracy of only 5%. Consistent with prior observations in both the macaque and marmoset models, we found that many PFC neurons exhibited activity related to the stimulus sample, during the delay period, and around the time of the behavioural response. In a subset of neurons, we observed distractor-mediated modulations of persistent delay period activity which were associated with a greater incidence of performance errors on the DML task. These findings reveal that marmoset WM is robust to distractor interference, and that the PFC mechanisms instantiating WM and distractor filtering are conserved in this primate species. Taken together, they support the common marmoset as a complementary model for investigating the contribution of PFC circuits to mnemonic and attentional processes.

Hierarchy in the brain emerges across spatial and temporal scales, enabling transformations from rapid sensory encoding to sustained cognitive control. Hierarchical gradients are well established in sensory systems. In contrast, the hierarchical organization of the primate motor cortex remains debated, partly due to its agranular architecture and the absence of clear laminar input-output projections, that obscures the distinction between feedforward and feedback pathways. In particular, the relative hierarchical position of the dorsal premotor cortex (PMd) and the primary motor cortex (M1) cannot be resolved from anatomy alone. To investigate their relative organization, we here adopted a multimodal approach using intrinsic timescales derived from both single-unit spiking activity (SUA) and local field potentials (LFPs) in macaques performing a delayed-match-to-sample reaching task. We found convergent evidence for inter-areal temporal hierarchy, with longer spiking timescales and smaller LFP aperiodic spectral exponents in M1. Across cortical depth, however, temporal organization depended on signal modality. LFP spectral exponents were significantly smaller in deep than superficial layers in both areas, and LFP-autocorrelation timescales were longer in deep layers in M1. In contrast, spiking activity did not show significant laminar differences in intrinsic timescales. Functionally, neurons with longer timescales exhibited more stable representations of the planned movement direction during motor preparation in PMd and slower temporal evolution of movement encoding during execution in both areas. In conclusion, multimodal temporal measures converge on the same hierarchical organization across these two motor areas, with M1 placed higher than PMd. Our study provides the first characterization of intrinsic spiking timescales across cortical layers in any cortical area and shows that laminar temporal organization depends on the neural signal analyzed. This divergence likely reflects their distinct physiological origins. Spikes capture neuronal output, whereas LFPs primarily reflect synaptic and dendritic population activity, potentially integrating differential contributions from apical and basal dendritic inputs.

Working memory (WM) provides a flexible but capacity-limited workspace for maintaining information over short intervals, whereas long-term memory (LTM) serves as a vast and enduring repository for preserving information over extended periods. Decades of research suggest that they are two distinct yet connected systems that together enable adaptive behavior. The link between WM and LTM may not be straightforward, however, as recent evidence has shown that activation-dependent competition among items in WM can weaken their representations in LTM. In the current study, we examined how dynamic competition among items for limited WM resources affects their retention in LTM. We induced competition between items by manipulating temporal expectations in a WM task with either a short (1 s) or a long (4 s) memory delay. Human participants (N = 20) initially prioritized items expected to be tested early, but shifted their priority to items expected to be tested later when the early test did not occur. Using electroencephalography (EEG) and multivariate pattern analysis (MVPA), we tracked the dynamic fluctuations in WM contents based on expected task relevance across the delay window. We linked these temporal profiles during WM with the long-term recognition performance of each item and found that forgetting was associated with a marked decrease in neural evidence for items deemed no longer relevant during the later delay period. These results demonstrate that WM representations fluctuate with temporal expectations and that the de-prioritization of items during WM maintenance is what drives their long-term forgetting.

Fluctuations in attentional states, such as mind-wandering (MW), are associated with critical variability in task performance. While fMRI studies highlight the opposing roles of task-positive (e.g., dorsal attention network) and task-negative (e.g., default mode network) systems, the electrophysiological mechanisms underlying these dynamics remain poorly understood. Using intracranial electrocorticography in humans performing a sustained attention task, we identified global oscillatory dynamics linked to attentional shifts. MW was characterized by (i) reduced theta ({theta}) and alpha ({square}) power, (ii) decreased aperiodic signal components, indicating a shift toward cortical inhibition, (iii) enhanced phase synchronization across networks, and (iv) strengthened {theta} phase-behavior correlations ({rho}). These features support a non-network-specific framework in which low-frequency {theta} dynamics--captured by both {theta} power and {rho}--are associated with attentional fluctuations, while aperiodic offset relates to attentional state indirectly through its association with {rho} (Structural Equation Modeling: power[-&gt;]state {beta} = -0.118, p = 0.002; {rho}[-&gt;]state {beta} = 0.246, p < 0.001; offset[-&gt;]{rho} {beta} = -0.222, p < 0.001). Our study provides a unified neurophysiological framework for understanding how spontaneous neural activity can drive attentional fluctuations and performance variability, with implications for research on attention, learning, and neuropsychiatric disorders.

Neural activity inevitably produces waste, which promotes neurodegeneration with topographic features. The glymphatic system is important for waste clearance. However, the spatial characteristics of glymphatic clearance across cortex and whether it interplays with neural activity in contribution to amyloidosis in human remain unexplored. Here, by intrathecal administration of gadolinium-based contrast agents, glymphatic influx and clearance patterns across cortex in 96 participants are depicted via Glymphatic MRI. Analyses integrating post-mortem transcriptomic profiles from Allen Human Brain Atlas indicate that, genes related with excitatory and inhibitory neurons, and pathways engaging in synaptic function were enriched in regions with faster glymphatic clearance. FALFF was calculated from resting-state fMRI to represent neural activity. At the regional level, based on a subgroup with rs-fMRI (N = 15), regional glymphatic clearance was positively coupled with spontaneous neural activity. Mismatch index, reflecting decoupling between spontaneous neural activity and glymphatic clearance function, turned out to be positively associated with regional severity of amyloidosis using open-source 11C-PiB dataset. Together, this study for the first time demonstrates the intricate interplays between neural activity and glymphatic dynamics from transcriptional to physiological level. The mismatch between these two processes may serve as an undescribed comprehensive mechanism promoting regional vulnerability to proteopathy and subsequent neurodegeneration in cortex.

Given the limited capacity of working memory (WM), prioritization is essential for efficient information processing. Whether prioritization acts primarily at encoding, or dynamically shapes representations during maintenance, is currently unclear. Here, we employed a two-item delayed-match-to-sample task and compared prioritization conditions in which the testing order of items was either known in advance or not. Behaviorally, prioritization selectively reduced guess rates, without affecting precision. Using multivariate pattern analysis, we decoded stimulus information from EEG voltage and indexed internal attention using alpha-band patterns. Prioritization did not alter decodable representations during encoding. During maintenance, however, prioritization enhanced both voltage-based decodability and alpha power-based decodability for the currently prioritized item. Mediation analyses further indicated that alpha-based attentional signals influenced behavior indirectly, via voltage-based representational strength, which is consistent with the idea that internal attention supports performance by strengthening prioritized representations during memory maintenance. Significance StatementWM is capacity-limited, requiring the prioritization of information most relevant to current task demands. Whether prioritization is established at encoding or emerges during maintenance, and how it improves working memory performance, remains unclear. Comparing conditions with and without advance priority knowledge, we found that prioritization occurred primarily during maintenance rather than encoding. We also found that prioritization improved performance by directing internal attention to prioritized items, strengthening their neural representations and increasing their accessibility. This finding provides insight into the flexibility of working memory in the updating of already-encoded information.

The hippocampus has been proposed to support visual processing and perception, challenging longstanding accounts that emphasize navigation or declarative memory. A key prediction of visual-processing accounts is that the hippocampus should exhibit similar visuospatial coding properties to those of higher-order visual neocortical areas, such as sensitivity to the size of visual stimuli and contralateral visual field biases. We tested for these properties using intracranial EEG to measure hippocampal neural activity during a retinotopic mapping task. The hippocampus exhibited characteristic slow ([~]2 Hz) and fast ([~]8 Hz) theta oscillations throughout the task. Fast theta was responsive to the presence but not the amount of visual stimulation. In contrast, slow theta did not generally respond to stimulus presence but scaled with the size of the visual stimulus, consistent with larger receptive fields. Slow theta also showed a contralateral bias, an effect that was specific to the right hippocampus. None of these effects were attributable to microsaccades or performance of the concurrent vigilance task. These findings provide electrophysiological evidence for visual field coding by human hippocampus, supporting accounts of hippocampal function that emphasize its role atop the visual hierarchy. Visual processing of this kind may combine with self-motion, memory, and other signals to support the broader spatial and mnemonic functions with which hippocampal theta oscillations have long been associated.

Glutamatergic neuronal synapses in the mouse neocortex mature during the first two months after birth. A key event during synaptic maturation is a change in short-term synaptic plasticity (STP), i.e. a switch from strong synaptic depression to a weaker depression or even facilitation. Glutamatergic pyramidal neurons located in the cortical layers II/III, layer V, and layer VI project axons through the corpus callosum where they release glutamate along their shafts and form glutamatergic synapses with oligodendrocyte precursor cells (OPCs). Here, we used single-cell electrophysiological recordings in brain slices to investigate synaptic plasticity at neuron-OPC synapses along axonal shafts in the white matter, and applied computation approaches to pinpoint the mechanisms of this plasticity. We found that during postnatal development of mice, there is a switch from short-term synaptic depression to short-term synaptic facilitation at glutamatergic neuron-OPC synapses in the corpus callosum. Synaptic delay of phasic neuron-OPC excitatory postsynaptic current shortens, and the amount of asynchronous release at neuron-OPC synapses decrease as animals mature, indicating that glutamate release becomes more synchronized. Our computational modelling suggests that both pre- and postsynaptic changes may contribute to the functional development and changes of plasticity at neuron-OPC synapses in the white matter. Taking together, our findings indicate that synaptic release machineries located at different sites along the same axon (i.e. axonal shaft in the white matter vs synaptic boutons in the grey matter) mature in a very similar fashion, STP occurs at both synaptic sites, and STP dynamics represent an important event during brain maturation.

Sudden and isolated sensory stimuli (SISS) engage the extralemniscal system and elicit widespread electrocortical responses in the brain. These responses, consisting of both time-domain transients and spectral changes, reflect a switch of the global brain state that likely prepares the organism for subsequent urgent behaviours. Crucially, SISS also elicit a short-latency phasic response in a key component of the extralemniscal system in the brainstem, the noradrenergic Locus Coeruleus (LC) nucleus. Such stimulus-evoked LC firing is associated with the electrocortical markers of extralemniscal activation. LC neurons also display burst-like firing spontaneously, i.e., without imposed sensory stimuli, for example, during quiet wakefulness, sleep, or anaesthesia. However, this phenomenon remains underexplored. We therefore measured, in freely behaving rats, the prefrontal electrocorticogram (ECoG) responses following spontaneous LC bursts. In addition, we compared these ECoG responses to those triggered by electrical LC stimulation or auditory SISS. We found that ECoG responses were proportional to the magnitude of the spontaneous LC bursts or microstimulation, and remarkably similar to those elicited by SISS. Finally, suppression of noradrenergic transmission with systemic clonidine administration attenuated the auditory-evoked ECoG response. These results suggest that LC plays a role in generating the transient brain state changes elicited by SISS.

The cerebellum plays a central role in generating temporal predictions from past sensory regularities, yet the temporal boundaries of this predictive capacity remain unclear. Using magnetoencephalography (MEG), we investigated somatosensory and cerebellar responses to omissions within rhythmic somatosensory stimulation trains across six inter-stimulus intervals (ISIs) ranging from 0.5 to 5.5 seconds. We hypothesised that cerebellar prediction signals would follow a logistic decay pattern, remaining robust at short ISIs before declining beyond a 2-4-second temporal threshold. As a first step, we validated the omission paradigm by confirming the expected SI and SII response pattern to stimulations and the preservation of the SII response to omissions. Cerebellar source reconstruction revealed consistent beta band (14-30 Hz) responses to omissions peaking at 40-50 ms post-omission in right lobule VI, replicating previous findings. Critically, cerebellar activation to omissions was compatible with a logistic decay pattern with increasing ISI, with the inflexion point estimated within the hypothesised 2-4-second window, though precise localisation of this threshold warrants further investigation. Together, these findings establish empirical boundaries for cerebellar temporal prediction, suggesting that the cerebellum operates as a precise but duration-limited internal clock with implications for understanding the brains timing mechanisms and their functional consequences for perception.

Emerging evidence suggests that hippocampus contributes to visual short-term memory (VSTM). However, the role of hippocampal ripple activity--brief high-frequency oscillations associated with memory replay--in supporting VSTM of naturalistic objects remains largely unknown. Here, using intracranial EEG recordings from human participants performing a delayed match-to-sample task, we found that hippocampal ripple rates progressively ramped up during the maintenance period and supported successful VSTM. More critically, hippocampal ripples were temporally coupled with the ripples in the lateral temporal lobe (LTL), and these coupled ripples were associated with the memory reactivation in the LTL. These findings provide direct evidence that hippocampal-neocortical interaction via coupled ripples supports VSTM, extending the hippocampal ripples role to short-term mnemonic processes.

Withdrawal statementThe authors have withdrawn their manuscript because it was posted without the approval of all authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.