Progress in Neurobiology

Previous work has proposed two potentials benefits of retrospective attention on working memory (WM): target strengthening and non-target inhibition. It remains unknown which hypothesis contributes to the improved WM performance, yet the neural mechanisms responsible for this attentional benefit are unclear. Here, we recorded electroencephalography (EEG) signals while 33 participants performed a retrospective-cue WM task. Multivariate pattern classification analysis revealed that only representations of target features were enhanced by valid retrospective attention during the retention, supporting the target strengthening hypothesis. Further univariate analysis found that mid-frontal theta inter-trial phase coherence (ITPC) and ERP components were modulated by valid retrospective attention and correlated with individual differences and moment-to-moment fluctuations on behavioral outcomes, suggesting that both trait- and state-level variability in attentional preparatory processes influence goal-directed behavior. Furthermore, task-irrelevant target spatial location could be decoded from EEG signals, indicating that enhanced spatial binding of target representation promotes high WM precision. Importantly, frontoparietal theta-alpha phase-amplitude-coupling was increased by valid retrospective attention and predicted the reduced randomly guessing rates. This long-range connection supported top-down information flow in engagement of frontoparietal networks, which might organize attentional states to integrate target features. Altogether, these results provide neurophysiological bases that retrospective attention improves WM precision through enhancing representation of target and emphasize the critical role of frontoparietal attentional network in the control of WM representations.

Power modulations in alpha oscillations (8-14Hz) have been associated with most human cognitive functions and psychopathological conditions studied. These reports are often inconsistent with the prevailing view of a specific relationship of alpha oscillations to attention and working memory (WM). We propose that conceptualizing the role of alpha oscillations in oculomotor control resolves this inconsistency. This proposition is based on a review of results across species (human Npooled=295, one non-human primate, honey bee N=5), experimental conditions (rest, attention, and working memory), and recording techniques (EEG, ECOG, eye-tracking, and MEG) that encourage the following relationships between alpha oscillations and eye-movement control: (i) saccade initiation prompts power decrease in brain circuits associated with saccadic control; (ii) the direction of a saccade is consistent with alpha lateralization, both during task and resting conditions; (iii) the phase of alpha activity informs saccade occurrence and biases miniature eye movements during fixation (e.g. fixational tremor); and (iv) oculomotor action differentiates WM load. A new theory on how alpha oscillations link oculomotor action to cognition is proposed. Generalizing across tasks and species: low oculomotor activity is associated with high alpha power and vice versa. Alpha oscillations regulate how long to look at a given target and how fast to saccade to a next. By ensuring steady gaze position, any potential input outside foveal vision is "suppressed".

Theta (4-10 Hz) oscillations seem well-suited for coordinating neural activity. Many studies have focused on thetas role in long-range coordination across brain regions (e.g., connectivity between the prefrontal cortex and the hippocampus). It remains unclear how theta coordinates neural activity more locally within prefrontal subareas. We examined neural activity in three frontal areas (i.e., dorsolateral prefrontal cortex (dlPFC), ventrolateral prefrontal cortex (vlPFC), and frontal eye fields (FEF)) as non-human primates categorized dot patterns. We found that theta flexibly coordinated spiking activity and higher-frequency oscillations within and between frontal areas. First, theta phase in all areas was coupled to spiking information in the FEF and seemed to gate information that was behaviorally relevant. Second, theta influences were routed in opposite directions depending on feedback. Theta flowed in a posterior direction to the FEF during choices and after correct outcomes. Theta influences reversed directionality and flowed in an anterior direction after incorrect outcomes. Third, theta organized nested cross-frequency, phase-amplitude interactions. Theta was coupled to beta (15-30Hz) oscillations, both within and between areas. Beta, in turn, was coupled to gamma (40-90Hz) oscillations, but mainly locally. Together, our results position theta as a critical mechanism that flexibly and dynamically coordinates neural activity within and across the frontal cortex. HIGHLIGHTS- Neural activity was recorded in three frontal areas as non-human primates categorized dot patterns. - Theta (4-10Hz) oscillations gated relevant information in spiking. - Theta influences were routed in opposite directions depending on feedback. - Theta organized nested cross-frequency interactions with beta (15-30Hz) and gamma (40-90Hz) oscillations. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/729810v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1b4a6a4org.highwire.dtl.DTLVardef@12886feorg.highwire.dtl.DTLVardef@1b6c08dorg.highwire.dtl.DTLVardef@11ba768_HPS_FORMAT_FIGEXP M_FIG C_FIG

Metacognition, the ability to introspectively monitor ones own performance, remains an area with poorly understood neural mechanisms, particularly regarding the intercommunication among various brain regions. Recent studies have identified the precuneus as a key region in mnemonic metacognitive tasks, while the hippocampus is recognized for its role in memory function. This study aimed to investigate the role of the precuneus and hippocampus in mnemonic metacognition by utilizing intracranial electrode recordings from patients with intractable epilepsy to analyze the correlational dynamics between these regions. Our findings revealed that high gamma activity serve as a key feature in both the precuneus and hippocampus for confidence judgment. Based on signal detection theory (SDT), we discovered that high gamma activity in the precuneus is significantly linked to type 2 sensitivity (meta-d), while hippocampal high gamma activity was primarily linked to type 1 sensitivity (d). Additionally, the correlation between high gamma activity in the hippocampus and precuneus was exclusively related to type 2 sensitivity (meta-d). Temporal analysis indicated that the hippocampus is initially engaged for the memory process, followed by its joint engagement together with the precuneus for confidence generation. These findings elucidate the distinct electrophysiological roles of the hippocampus and precuneus in mnemonic metacognition, providing deeper insights into the neural mechanisms underlying this cognitive process.

The prefrontal cortex (PFC) plays a key role in selecting, maintaining and representing sensory information, and in its integration with our current internal goals and expectations, implementing such cognitive processes as executive functions, attention, decision making and working memory. Performing computation over all of these functional cognitive processes and dynamically shifting from one to the other based on task demands requires a complex functional organization and a high degree of coding flexibility. The PFC cells show a non-linear mixed selectivity characterized by specific tuning for multiple task- and behaviour related parameters. This non-linear mixed selectivity thought to allow for a high-dimensional representation of information. Here, we asked if the PFC is mainly involved in specific task-parameters representation, or if it additionally holds a higher order representation for task-identity. We thus trained two macaques to perform three different tasks: a memory guided saccade task and two detection tasks involving different attention mechanisms. Multi-unit activity was recorded in the frontal eye field, bilaterally, while monkeys performed these three tasks in a same session. Using demixed Principal Component Analysis, we found a two-dimensional neural state that characterized each of these tasks. The lower dimensional representation of the activity recorded during the performance of the two attentional tasks were more similar to each other than to the memory-guided saccade task. Furthermore, we report that task and spatial information are non-linearly mixed, a signature of a high-dimensional neural representation. Overall, this indicates that PFC encodes task identity information and flexibly adjusts its sensory processes as a function of the specific ongoing task. Significance StatementOne long lasting question in cognitive neuroscience is whether PFC mainly represents the different parameters that are needed to perform any given task, or if it additionally holds a higher order representation for task-identity. We recorded from the macaque frontal eye fields while monkeys performed a memory guided saccade task and two detection tasks involving different attention mechanisms. We found a task-identity neural state in which the two attentional tasks were represented similarly to each other but differently from the memory-guided saccade task. We also report that task and spatial information are non-linearly mixed, a signature of a high-dimensional neuronal representation. Overall, this indicates that PFC encodes task identity information and flexibly adjusts its sensory processes as a function of the specific ongoing task.

Electroencephalographic (EEG) studies of human quiet stance demonstrate beta-band event-related desynchronization (beta-ERD) during the micro-fall phase of postural sway, followed by event-related synchronization (beta-ERS; post-movement beta rebound) during the micro-recovery phase. These modulations correlate with intermittent ankle muscle activation that exploits the stable manifolds of an unstable upright equilibrium; however, the underlying neurocircuit mechanisms remain elusive. Here, we investigated this rhythmogenesis using an embodied spiking neural network model of the cortico-basal ganglia-thalamic (CBGT) circuitry integrated with a physical inverted pendulum. In this closed-loop system, continuous sensory feedback is integrated into the striatum, while the motor cortex executes decisions via drift-diffusion-like population competition, where the decision time (DT) represents the intermittent control-off period. We demonstrate that simulated cortical LFPs exhibit characteristic sway-locked beta-ERD and beta-ERS exclusively when corticostriatal synaptic weights are functionally balanced to implement intermittent control. Conversely, continuous stiffness control fails to replicate these modulations, sustaining flat, non-switching network states. Structural dissections reveal that while sensory drive remains continuous, phase-locked beta modulations are an emergent property generated fundamentally by bidirectional thalamocortical loops and the intrinsic dynamics of the GPe-STN pacemaker circuit. Our findings suggest that CBGT-mediated, phase-locked beta activity serves as a hallmark of healthy intermittent motor selection. This computational framework provides a crucial bridge linking pathological alterations in basal ganglia dynamics and the loss of behavioral intermittency to the postural impairments observed in clinical populations such as Parkinson's disease.

Retaining information in working memory (WM) is an active process that requires neural activity within and between regions. The human amygdala (AMY) and hippocampus (HPC) are known to play crucial roles in WM processing. Although electrophysiological studies have revealed that the HPC supports multi-item maintenance in a load-dependent manner, the characteristics of the AMY and the circuit-level mechanisms underlying AMY-HPC interactions remain largely unexplored. To address this knowledge gap, intracranial EEG recordings from the AMY and HPC in nine epileptic patients were employed to evaluate intraregional neural representations and interregional communications during maintenance under different non-emotional WM loads. High load enhanced low-frequency power and intraregional theta-gamma phase-amplitude coupling (PAC) in the AMY and HPC. At the network level, a high load elicited an increase in the strength of the HPC theta phase modulation, which entrains the AMY gamma amplitude. Furthermore, a high load increased AMY-anterior HPC (aHPC) theta phase synchrony and directional connectivity strength from the aHPC to the AMY. Conversely, posterior HPC (pHPC)-AMY synchrony was not affected by load variations. Overall, these findings highlight the importance of the AMY in non-emotional WM tasks and provide new insights into the neurophysiological basis of AMY-HPC interactions during WM maintenance.

Functional neuronal correlations between pairs of neurons are thought to play an important role in neuronal information processing and optimal neuronal computations during attention, perception, decision-making and learning. Here, we report dynamic changes in prefrontal neuronal noise correlations at multiple time-scales, as a function of task contingencies. Specifically, we record neuronal activity from the macaque frontal eye fields, a cortical region at the source of spatial attention top-down control, while the animals are engaged in tasks of varying cognitive demands. First, we show that noise correlations decrease as cognitive engagement and task demands increase, both across tasks and within-trials. Second, we demonstrate, for the first time, rhythmic modulations of noise correlations in the alpha and beta frequency ranges that account both for overt behavioral performance and for layer specific modulations in spike-field coherence. All this taken together demonstrates a strong functional role of noise correlations in cognitive flexibility.

The ability to deliberately overwrite ongoing automatic actions is a necessary feature of adaptive behavior. It has been proposed that the supplementary motor areas (SMAs) operate as a controller that orchestrates the switching between automatic and deliberate processes by inhibiting ongoing behaviors and so facilitating the execution of alternative ones. In addition, previous studies support the involvement of SMAs theta waves (4-9 Hz) in cognitive control. However, the exact role of such oscillatory dynamics and their contribution to the control of action are not fully understood. To investigate the mechanisms by which the SMAs support direct control of deliberate behavior, we recorded intracranial electroencephalography (iEEG) activity in humans performing a motor sequence task. Subjects had to perform a "change of plans" motor task requiring habitual movements to be overwritten at unpredictable moments. We found that SMAs were exclusively active during trials that demand action reprogramming in response to the unexpected cue but were silent during automatic action execution. Importantly, SMAs activity was characterized by a distinct temporal pattern, expressed in a stereotypical phase alignment of theta oscillations. More specifically, single trial motor performance was correlated with the trial contribution to the global inter-trial phase coherence, with higher coherence associated with faster trials. In addition, theta phase modulated the amplitude of gamma oscillations, with higher cross-frequency coupling in faster trials. Our results suggest that within frontal cortical networks, theta oscillations could encode a control signal that promotes the execution of deliberate actions.

How do we choose a particular action among equally valid alternatives? Non-human primate findings have shown that decision-making implicates modulations in unit firing rates and local field potentials (LFPs) across frontal and parietal cortices. Yet the electrophysiological brain mechanisms that underlie free choice in humans remain ill defined. Here, we address this question using rare intracerebral EEG recordings in surgical epilepsy patients performing a delayed oculomotor decision task. We find that the temporal dynamics of high gamma (HG, 60-140 Hz) neural activity in distinct frontal and parietal brain areas robustly discriminate free choice from instructed saccade planning at the level of single trials. Classification analysis was applied to the LFP signals to isolate decision-related activity from sensory and motor planning processes. Compared to instructed saccades, free choice trials exhibited delayed and longer-lasting HG activity. The temporal dynamics of these sustained decision-related responses distinguished deliberation-related from working memory processes. Taken together, these findings provide the first direct electrophysiological evidence in humans for the role of sustained high-frequency neural activation in fronto-parietal cortex in mediating the intrinsically driven process of freely choosing among competing behavioral alternatives. HighlightsO_LIFirst intracerebral recordings in humans performing an oculomotor decision-making task C_LIO_LIMachine learning analytics unravel underlying spectral and temporal brain dynamics C_LIO_LIFree choice trials exhibit sustained fronto-parietal high gamma (HG) activity during the delay C_LIO_LIMaking a decision and maintaining it in working memory are associated with distinct sustained HG dynamics C_LI

BackgroundPsilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state dynamic functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects. AimEvaluate the association between resting-state dynamic functional connectivity (dFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans. MethodsFifteen healthy individuals completed the study. Before and at multiple time points after psilocybin intake, we acquired 10-minute resting-state blood-oxygen-level-dependent functional magnetic resonance imaging scans. Leading Eigenvector Dynamics Analysis (LEiDA) and diametrical clustering were applied to estimate discrete, sequentially active brain states. We evaluated associations between the fractional occurrence of brain states during a scan session and PPL and SDI using linear mixed-effects models. We examined associations between brain state dwell time and PPL and SDI using frailty Cox proportional hazards survival analysis. ResultsFractional occurrences for two brain states characterized by lateral frontoparietal and medial fronto-parietal-cingulate coherence were statistically significantly negatively associated with PPL and SDI. Dwell time for these brain states was negatively associated with SDI and, to a lesser extent, PPL. Conversely, fractional occurrence and dwell time of a fully connected brain state was positively associated with PPL and SDI. ConclusionOur findings suggest that the acute perceptual psychedelic effects induced by psilocybin may stem from drug-level associated decreases in the occurrence and duration of lateral and medial frontoparietal connectivity motifs in exchange for increases in a uniform connectivity structure. We apply and argue for a modified approach to modeling eigenvectors produced by LEiDA that more fully acknowledges their underlying structure. Together these findings contribute to a more comprehensive neurobiological framework underlying acute effects of serotonergic psychedelics. HighlightsO_LIWe examined psilocybin effects on resting-state fMRI dynamic functional connectivity C_LIO_LIDiametrical clustering described as improved strategy for LEiDA-defined brain states C_LIO_LIIndividual brain state dynamics defined by fractional occurrence and dwell time C_LIO_LITwo frontoparietal states and a fully connected brain state affected by psilocybin C_LIO_LIBrain state dynamics associated with psilocin level and subjective experience C_LI

The frontal eye field (FEF) is a cortical area classically associated with spatial attention, perception, and oculomotor functions. FEF exhibits complex response properties through mixed selectivity neurons, allowing a high dimensional representation of the information. However, recent studies have shown that FEF encodes information in a low-dimensional regime hence limiting the coding capacity of the neural population. How the FEF encodes multiple sources of information with such limited encoding capacity remains elusive. To address this question, we trained two macaques to perform a visual attention task while we recorded FEF neuronal activity using multi-contact electrodes. FEF neurons encoded task- (time in the trial; CTOA) and behaviour- (reaction time, RT; focus of attention, TA) related parameters prior to the target onset. We found a clear modulation of the RT and TA as a function of the CTOA. Using dPCA, we characterized the functional relationship between neural populations associated with each parameter and investigated how this functional relationship predicts behaviour. We found that CTOA variability was associated with two different components the activation of which was correlated with the TA and the RT, respectively. These CTOA-related components were non-orthogonal with the RT and TA-related components, respectively. These results suggest that, when different sources of information are implemented during task performance, they show a very precise geometrical configuration in non-orthogonal components, which allows a high capacity of information coding at a cost of modulating both the capacity of the monkey to use attention information and its responsiveness toward external stimuli.

Flickering light stimulation has emerged as a promising non-invasive neuromodulation strategy to alleviate neuropsychiatric disorders. However, the lack of a neurochemical underpinning has hampered its therapeutic development. Here, we demonstrate that light flickering triggered an immediate and sustained increase (up to 3 hours after flickering) in extracellular adenosine levels in the primary visual cortex and other brain regions, as a function of light frequency, intensity, and wavelength, with maximal effects observed at 40 Hz frequency. We discovered cortical (glutamatergic and GABAergic) neurons, rather than astrocytes, as the cellular source, and intracellular adenosine generation from calcium influx-triggered, AMPK- associated energy metabolism pathways (but not SAM-transmethylation or salvage purine pathways) and adenosine efflux mediated by equilibrative nucleoside transporter-2 (ENT2) as the molecular pathway responsible for extracellular adenosine generation. Importantly, 40 Hz light flickering for 30 min enhanced sleep in mice in a frequency-dependent manner. This somnogenic effect was absent in mice lacking ENT2 but replicated by administering adenosine to the visual cortex. Brief 40 Hz light flickering also promoted sleep in children with insomnia by decreasing sleep onset latency, increasing total sleep time, and reducing waking after sleep onset. Collectively, our findings establish adenosine signaling via ENT2 as the neurochemical basis for 40 Hz flickering-induced sleep and unravel a novel and non-invasive treatment for insomnia, a condition that affects 20% of the world population.

Basal ganglia rhythms have mainly been studied in the beta band (12-30 Hz), a hallmark of Parkinsons disease (PD), while gamma oscillations (30-100 Hz) in the subthalamic nucleus (STN) have emerged as alternative markers for guiding adaptive deep brain stimulation. However, their underlying mechanisms remains unclear. Using a spiking network model of the basal ganglia, we identified two distinct gamma rhythms: a high-frequency gamma in pallidal (GPe-TI) neurons and a slower gamma in D2 medium spiny neurons (MSNs), both generated through self-inhibition. Under simulated parkinsonian condition, GPe-TI gamma intensity remained stable. In contrast, D2 MSN gamma emerged only in pathological conditions and was strongly modulated by beta activity in both intensity and frequency. Although STN did not generate gamma oscillations directly, gamma activity from GPe-TI population was reflected in simulated STN local field potentials. These results clarify the circuit origins of gamma rhythms and their modulation in PD.

A central question in sensorimotor neuroscience is how sensory inputs are mapped onto motor outputs to enable swift and accurate responses, even in the face of unexpected environmental changes. In this study, we leverage cortico-motor phase synchronization as a window into the dynamics of sensorimotor loops and explore how it relates to online visuomotor control. We recorded brain activity using electroencephalography (EEG) while participants performed an isometric tracking task that involved transient, unpredictable visual perturbations. Our results show that synchronization between cortical activity and motor output (force) in the alpha band (8-13 Hz) is associated with faster motor responses, while beta-band synchronization (18-30 Hz) promotes more accurate control, which is in turn linked to a higher likelihood of obtaining rewards. Both effects are most pronounced immediately before perturbation onset, underscoring the predictive value of cortico-motor phase synchronization for sensorimotor performance. Single-trial analyses further reveal that deviations from the preferred cortico-motor phase relationship are associated with longer reaction times and larger errors, and these phase effects are independent of power effects. Thus, beta-band synchronization may reflect a cautious, reward-oriented control strategy, while alpha-band synchronization enables quicker, though not necessarily efficient, motor responses, indicating a complementary, more reactive control mode. These results highlight the finely tuned nature of sensorimotor control, where different aspects of sensory-to-motor transformations are governed by frequency-specific neural synchronization on a moment-to-moment basis. By linking neural dynamics to motor output, this study sheds light on the spectrotemporal organization of sensorimotor networks and their distinct contribution to goal-directed behavior.

Working memory (WM) is the ability to actively maintain information for a short time and is central to human behavior. Rodent studies have proposed that hippocampal-entorhinal communication supports WM maintenance. However, the exact neural mechanisms of this interaction in WM remains unclear in humans. To address these questions, we combined machine learning analyses with intracranial electroencephalography (iEEG) recordings from the hippocampus and the entorhinal cortex (EC) in human participants, who maintained a set of letters in their WM. We found that WM maintenance was accompanied by elevated bidirectional hippocampal-EC information exchange via the theta band (2-8 Hz) and bidirectional cross-region theta-gamma phase-amplitude coupling (PAC). Further decoding analyses showed that the unidirectional inter-regional communication, with both theta oscillations in the hippocampus modulating EC gamma activity and theta band-coordinated information flow from the hippocampus, could decode correct performance at the level of participants. Taken together, our results demonstrate that theta functional coupling in the hippocampal-EC supports the maintenance of WM information via a specific pattern of frequency and direction. This connectivity-based coding could shed light on the neural mechanisms of WM processing. SignificanceRecent studies suggest a role for the hippocampus in working memory. How does the hippocampus coordinate with other brain regions to retain working memory information? The entorhinal cortex (EC) is the main gateway for information between the hippocampus and neocortex. To delineate whether (and how) the hippocampus and the entorhinal cortex interact during working memory and whether such interaction supports successful working memory, we used machine learning analyses of human intracranial EEG recordings while patients performed working memory tasks. Our results suggest that the human hippocampal-EC circuit supports working memory and is maintained in specific connectivity patterns, with a theta band (2-8 Hz)-coordinated unidirectional influence from the hippocampus to the EC. Our findings reveal that dynamic unidirectional interactions within the hippocampal-EC circuit underlie working memory and can contribute to a mechanistic circuit understanding of working memory.

As routine and lower demand cognitive tasks are taken over by automated assistive systems, human operators are increasingly required to sustain cognitive demand over long periods of time. This has been reported to have long term adverse effects on cardiovascular and mental health. However, it remains unclear whether prolonged cognitive activity results in a monotonic decrease in the efficiency of the recruited brain processes, or whether the brain is able to sustain functions over time spans of one hour and more. Here, we show that during working sessions of one hour or more, contrary to the prediction of a monotonic decline, behavioral performance in both humans and non-human primates consistently fluctuates between periods of optimal and suboptimal performance at a very slow rhythm of circa 5 cycles per hour. These fluctuations are observed in both high attentional (in non-human primates) and low attentional (in humans) demand conditions. They coincide with fluctuations in pupil diameter, indicating underlying changes in arousal and information-processing load. Accordingly, we show that these rhythmic behavioral fluctuations correlate, at the neurophysiological level, with fluctuations in the informational attention orientation and perception processing capacity of prefrontal neuronal populations. We further identify specific markers of these fluctuations in LFP power, LFP coherence and spike-field coherence, pointing towards long-range rhythmic modulatory inputs to the prefrontal cortex rather than a local prefrontal origin. These results shed light on the resilience of brain mechanisms to sustained effort and have direct implications on how to optimize high cognitive demand working and learning environments.

Reward expectancy shapes behavioral performance by coordinating the allocation of cognitive resources, which incorporates the involvement of the anterior insular cortex (AIC). To investigate the electrophysiological mechanisms of the AIC during reward expectancy, we collected intracranial electroencephalographic data from epilepsy patients undergoing clinical monitoring. Subjects navigated a virtual T-maze containing rewards at three predetermined locations. We focused on the period immediately before entering the reward zone, termed the reward expectancy stage. During this stage, we identified the reward-specific brain patterns (RBPs) that were preactivated in the AIC. This pre-activation preceded the emergence of robust phase-amplitude coupling (PAC), where theta oscillations (5-7 Hz) modulated gamma activities (75-110 Hz). The PAC strength correlated positively with the pre-activation level of RBPs, implying the potential role of oscillatory coordination in amplifying preactivated reward representations. Strikingly, this PAC effect exhibited a specific temporal structure that peak gamma activity became progressively coupled to earlier theta phases as reward approached, mirroring the theta phase precession phenomenon previously observed in frontal and temporal lobes. We refer to this dynamic as phase-precession-like effect (PPLE). Moreover, subjects exhibiting PPLE in the AIC presented greater trial-by-trial improvements in response latency. Taken together, these findings shed light on the electrophysiological mechanisms of the AIC underlying reward expectancy.

Idiopathic/isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of alpha-synucleinopathies. Cortical and sub-cortical brain modifications begin years before the emergence of overt neurodegenerative symptoms. To better understand the pathophysiological process impacting the brain from the prodromal to the overt stage of alpha-synucleinopathy, it is essential to assess iRBD patients over time. Recent evidence suggests that the human brain operates at an operating point near a critical phase transition between subcritical and supercritical phases in the systems state space to maintain cognitive and physiological performance. In contrast, a deviation from the critical regime leading to altered oscillatory dynamics has been observed in several pathologies. Here, we investigated if the alpha-synucleinopathy produces a deviation of the operating point already evident in the prodromal phase and if this shift correlates with biological and clinical disease severity. We analyzed a dataset of 59 patients with iRBD (age 69.61 {+/-} 6.98, 50 male) undergoing resting-state high-density EEG, presynaptic dopaminergic imaging, and clinical evaluations. Thirty-one patients (age 72.41 {+/-} 7.05, 31 male) also underwent clinical and instrumental follow-up (mean follow-up period 25.85 {+/-} 10.20 months). To localize the individual operating points along the excitation-inhibition (EI) continuum, we assessed both measures of neuronal EI balance and measures of critical brain dynamics such as long-range temporal correlation (LRTCs) and neuronal bistability in spontaneous narrow-band oscillations. Finally, we correlated critical brain dynamics and EI balance metrics with phase synchronization, nigro-striatal dopaminergic functioning, and clinical performances. Compared to 48 healthy subjects (age 70.25 {+/-} 10.15, 23 male), iRBD patients showed higher values of LRTCs and bistability in the 2-7 Hz band at diagnosis. Patients who eventually phenoconverted to overt alpha-synucleinopathy exhibited a more excitation-dominated (fEI > 1) condition than stable iRBD patients in 5-7 Hz. This higher excitation also directly correlated with phase synchronization in 2-7 Hz, further suggesting a shift of the operating point toward a supercritical state with the disease progression. Moreover, excitation-dominated state and low bistability were associated with deterioration of the nigro-striatal dopaminergic function and tended to correlate with stronger clinical symptoms. In conclusion, this study shows for the first time a deviation of the working point from inhibition-to excitation-dominated states along the continuum from prodromal to overt phases of the disease. These cortical brain dynamics modifications are associated with nigro-striatal dopaminergic impairment. These results increase our knowledge of the physiopathological process underlying alpha-synucleinopathies since prodromal stages, possibly providing new clues on disease-modifying strategies.

Flexible behaviour requires decision-making that integrates both perceptual and mnemonic-related information. While the dorsal premotor cortex (PMd) is known to support decision-making based on perceptual computations, its contributions to decisions based on mnemonic information for motor planning are underexplored. Here, investigating local field potential (LFP) oscillations in PMd of monkeys performing a transitive inference task required the formation and retrieval of mnemonic representations of an arbitrarily defined rank order among perceptual items. Our results highlight that a dynamic interplay between lower frequencies (Theta, Alpha, Beta) and high-Gamma oscillatory activity of LFP reflects a mechanism for accessing and manipulating memory-related information underlying decision-making. These findings provide evidence that the PMd plays a role in multiplexing both perceptual and mnemonic information, extending its competence beyond the association of perceptual input with motor decisions.