EEG/ECoG/EMG publications

Music listening is one of the most compelling and rewarding activities humans engage in spontaneously. But what exactly catches people”s attention when listening to music remains unclear. Musicologists have argued that tension - release dynamics in music constitute crucial features of the listening experience. They arise from the intertwining of different low-level and high-level features and sit at the core of music enjoyment by engaging listeners dynamically. This study aims to characterize the relationship between tension dynamics and engagement during naturalistic music listening. Using canonical correlation analysis, we decoded the music envelope from EEG and ECoG responses and found that musical tension patterns, as reported by listeners, were predictive of fluctuations in the coupling between the music and the neural response. Importantly, tension dynamics were significantly correlated with neural measures of envelope tracking even after controlling for loudness and musical expectations, confirming the specific and crucial role of musical tension in engaging listeners. These results shed new light on how musical structure gives rise to internal response modulations that, in turn, dynamically reflect musical engagement. This interplay may underlie the pervasive and emotionally rewarding nature of music. Significance Statement This work addresses a fundamental question in cognition: how engagement dynamically modulates complex auditory input processing. We investigate this issue within the well-controlled yet ecologically valid context of music perception. At the core of the musical experience lies the perception of tension – the shifting sense of expectancy, instability, and resolution that guides listening across time. We show that fluctuations in musical tension, shaped by musical structure, reliably predict modulations of auditory engagement, thereby illuminating an understudied phenomenon: what makes music engaging.

Background With age, even mild acoustic injuries can accumulate - ultimately leading to a characteristic clinical picture of age-related hearing loss with the risk of cognitive decline. Age-related hearing loss is currently attributed to the loss of a most vulnerable auditory fiber type contributing to hearing in background noise. Here, we investigated the potential of a new drug, a more stable chemical variant of Dendrogenin B (DX243) that is predicted to display a protective function on neurite outgrowth, rather than on cell survival. Methodology In the rat animal model, DX243 was tested on hearing thresholds, cortical local field potentials (LFP), auditory steady-state responses (ASSR), auditory brainstem responses (ABR), growth function of notched-noise stimuli, inner hair cell (IHC) ribbon numbers, and multi-click pulse responses (MCP) before and after auditory trauma (AT). Results No auditory evoked LFP response changes were seen in the prefrontal cortex, visual cortex, or hippocampus. In contrast, a permanent decline of auditory evoked LFP amplitudes in the auditory cortex (AC) was measured 2 weeks after AT. Daily injection of DX243 for 2 weeks prevented the AT-induced decline in LFP activity, a protective effect that continued for 6 weeks following the final injection. Through a protective effect of DX243 on a trauma-induced decline of LFP in response to amplitude-modulated tones >80 Hz, a subcortical origin of the drug-effect was suggested. DX243 showed no effect on hearing sensitivity and did not affect subcortical processing of sound features that depend on phase-locking at the stimulus onset (e.g., near-threshold ASSR responses, close-to-threshold ABR growth functions, or spontaneous cortical LFP responses). However, with the same dose-response dependency as shown for cortical LFP effects, DX243 significantly protected from AT-induced decreases in ABR growth functions for loud sound stimuli and in background noise, protected from AT-induced loss of IHC ribbons and AT-induced decline of fast ABRs with decreasing time intervals. Conclusion These findings suggest DX243 as a novel neuroprotective drug, that specifically protects auditory fibers contributing to the coding of the temporal envelope and detection of tones in masking noise, tasks of our auditory senses, both of which, if they fail, lead to age-related speech-in-noise comprehension deficits.

Introduction The abrupt cessation of chronic benzodiazepine administration is associated with the development of withdrawal symptoms like increased susceptibility to seizures or seizure development in both animals and humans. Although withdrawal phenomena have been studied in detail in adult animals, information about their development and nature in the immature brain is lacking. Substantial experimental evidence suggests that exposure to BZDs early in life permanently alters brain circuitry and functions. However, the possible long-term modification of seizure propensity has not yet been studied. Methods Clonazepam (CZP) was injected into rat pups daily at a dose of 1 mg/kg for five consecutive days, starting on postnatal day 7 (P7) and continuing until P11. Seizure susceptibility was assessed using a pentylenetetrazol (PTZ)-induced seizure model. PTZ induces three types of seizures in rodents that differ by developmental profile and manifestations: convulsive myoclonic seizures (mS) and generalized tonic-clonic seizures (GTCS), and absence-like rhythmic spike-and-wave EEG activity (RMA). Seizures were induced with a single threshold dose of 50–60 mg/kg on days 2, 4, 7, 10, or 14, or with three additive doses of 20 mg/kg on days 7 and 14, or 3 months after the end of treatment. Convulsions accompanying mS and GTCS were detected behaviorally, and RMA was detected in EEG recordings. Results The effects of early-life CZP exposure on susceptibility to PTZ-induced seizures were highly dependent on the interval after treatment cessation and the seizure type. Cessation of CZP after a single PTZ threshold dose resulted in an increase in seizure severity compared to controls that was driven by an increased incidence of GTCS lasting 1 week (up to P18). Early-life CZP exposure led to decreased latency to the first RMA and increased RMA frequency after the first PTZ dose of 20 mg/kg in adult (P90) animals, but it did not change RMA parameters in juvenile rats. Conclusion Abruptly ceasing clonazepam administration in infant rats results in the development of withdrawal phenomena, represented by a striking increase in seizure propensity. Interestingly, transient augmentation of GABAergic inhibition during critical periods of synaptogenesis and neural network formation and maturation permanently modifies susceptibility to PTZ-induced epileptiform activity.

Excessive daytime sleepiness, i.e., the inability to sustain wakefulness during the day, is a common Parkinson's disease (PD) non-motor symptom. Elevated cortico-basal ganglia beta oscillatory power (8-35 Hz) is a pathophysiological signature of PD motor signs. The relationship between beta oscillatory power and daytime sleepiness, however, remains unclear. Here, we examined the relationship between beta power and daytime vigilance in parkinsonian nonhuman primates. We administered dopaminergic medication to alter cortico-basal ganglia beta power and measured its effect on daytime vigilance. The beta power from motor cortex (MC) and subthalamic nucleus (STN), and wake quantity were derived in the following conditions: OFF-medication, ON-medication, and decay of medication effect. STN low-beta (8-20 Hz) power negatively correlated with wake quantity, suggesting that elevated STN low-beta power could disrupt sustenance of wakefulness. The cortical low-beta power did not correlate with wakefulness. Interestingly, STN and MC high-beta (21-35 Hz) power positively correlated with wake quantity. Our data provide evidence for an association between beta power and daytime vigilance in parkinsonism in addition to its known relationship with PD motor signs. These findings could inform targeted treatments to promote wakefulness in PD by selectively suppressing (e.g., low-beta) and/or amplifying (e.g., high-beta) cortico-basal ganglia beta oscillatory power.

The Rubber Voice Illusion is an auditory analogue of the classic Rubber Hand Illusion, a “mind-trick” for the voice. When speakers hear a stranger’s utterances that are perfectly time‑locked and syllable‑matched to their own voice, many momentarily adopt that alien voice as self‑generated. We used this illusion to probe the integrity of predictive auditory mechanisms across the psychosis continuum. Sixty healthy adults completed three Talk‑Listen conditions while high‑density EEG was recorded: veridical (live playback of own voice), stranger‑match (congruent stranger voice) and stranger‑mismatch (incongruent). Behaviorally, only the congruent condition evoked a sense of Ownership and Agency over the stranger’s voice, paired with an upward shift in fundamental frequency toward the higher-pitched stranger voice - an implicit indication of voice adaptation. Neurophysiologically, the canonical speaking-induced suppression was replicated, and suppression was significantly smaller in participants who scored high on Peters et al. Delusions Inventory. In controls, greater pitch shift was associated with stronger neural suppression, suggesting a functioning self-suppression mechanism; conversely, in high-schizotypy individuals, the relationship reversed, despite pitch shifting toward the stranger’s pitch, they exhibited reduced suppression, indicating decoupling between motor output and sensory prediction. The study provides further evidence to the intricate relationship of neural mechanisms underlying self-generated actions with sensory processing in the psychosis continuum.

Psychedelics lead to profound changes in subjective experience and behaviour, which are typically conceptualised in psychological terms rather than corresponding to an altered brain state or a distinct state of vigilance. Here, we performed chronic electrophysiological recordings from the neocortex concomitant with pupillometry in freely moving adult male mice following an injection of a short-acting psychedelic 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT). We report an acute induction of a dissociated state, characterised by prominent slow oscillations in the cortex and marked pupil dilation in behaviourally awake, moving animals. REM sleep was initially markedly suppressed, but was overcompensated in the subsequent 48 hours, while administration of 5-MeO-DMT immediately after sleep deprivation attenuated the subsequent rebound of sleep slow-wave activity. We argue that the occurrence of a dissociated state combining features of waking and sleep may fundamentally underpin the known and hypothesised effects of psychedelics — from dream-like hallucinations to reopening of the critical period for plasticity.

There is growing evidence that perceptual difficulties associated with age-related hearing loss are not solely due to cochlear damage and are exacerbated by central nervous system changes. We examined electrophysiological (EEG) responses to clicks and diffusion kurtosis imaging in 49 older (29 female) and 26 younger (20 female) adults to determine the extent to which auditory nerve (AN) deficits in older adults contributed to functional and structural changes throughout the auditory system. Older adults exhibited smaller AN responses, similar brainstem responses, and larger auditory cortex (AC) responses, demonstrating progressive "central gain." Audiometric thresholds were not predictive of EEG measures. Reduced AN function predicted deficits in cortical microstructure (lower AC fractional anisotropy) in older adults, consistent with microstructure degeneration. These lower fractional anisotropy values in the AC of older adults also predicted larger AC responses and more central gain. Older adults exhibited significantly lower AC fractional anisotropy and kurtosis fractional anisotropy coupled with higher mean and radial diffusivity compared to younger adults. AC fractional anisotropy, radial diffusivity, axial diffusivity, and mean diffusivity were all significant predictors of speech-in-noise (SIN) recognition in older adults. The results suggest that reduced afferent input in older adults not only results in functional changes throughout the auditory system consistent with progressive gain but also contributes to deficits in AC structure beyond those explained by age alone, contributing to SIN recognition deficits. Understanding the complex effects of age, reduced AN input, central gain, and AC microstructure on SIN recognition may provide potential therapeutic targets for intervention.

Auditory evoked responses undergo notable changes during childhood, likely reflecting modifications in synaptic signaling in the auditory cortex. Particularly robust response, observed around 200 to 300 ms post stimulus (N/M250), has been consistently reported in children but is absent in adults. This long-latency response, evoked even in passive listening conditions, may indicate heightened sensory pathway responsiveness, facilitating experience-driven cortical plasticity. However, it remains unclear whether this delayed activation pattern is an intrinsic, species-general feature of brain development. We recorded cortical auditory evoked responses to monaural sine-wave tones/click sounds in 3 age groups (preadolescents, adolescents, and young adults) of human subjects and rats. Following short-lived early responses, both species exhibited a long-latency (150 to 450 ms) response in the auditory cortex. In both species, the relative amplitude of the long-latency response, compared to early responses, was increased in younger individuals. In human children, single-trial analysis demonstrated more consistent trial-by-trial timing of the response in this later time window than in the adult-typical 100-ms response in the earlier time window. Given its emergence in purely passive conditions, and across species, the robust current activity in late time window could represent a distinct synaptic event and may serve as a marker of the maturational stage, particularly in GABAergic cortical circuits.

Speech production entails several processing steps that encode linguistic and articulatory structure, but whether these computations correspond to spatiotemporally discrete patterns of neural activity is unclear. To address this issue, we use electrocorticography to directly measure the brains of neurosurgical participants performing an interactive speech paradigm. We observe a broad range of cortical modulation profiles, and subsequent clustering analyses establish that responses comprised distinct classes associated with sensory perception, planning, motor execution, and task-related suppression. These activity classes are also localized to separate neural substrates, indicating their status as specialized networks. We then parse dynamics in the planning and motor networks using unsupervised dimensionality reduction, which reveals subnetworks that are sequentially active throughout preparation and articulation. These results therefore support and extend a localizationist model of speech production where cortical activity "flows" within and across discrete pathways during language use.

The mismatch response (MMR) is a critical neural indicator of the discrimination of speech contrasts. Previous research has demonstrated that language experience can affect MMRs: speech contrasts in one’s native language differ from nonnative speech contrasts. This effect is observed as early as 11–12 months, but not at 6–7 months, reflective of early learning of speech sounds. Yet, many challenges remain when using MMRs to study speech learning in infants, including prolonged recording time, inefficient use of data, and a lack of reconciliation of MMR recorded using different technologies (i.e., EEG vs. magnetoencephalography [MEG]). Using an improved recording paradigm and analysis approach, the current study addressed these challenges by examining (1) whether MEG-MMR is linked to the well-established EEG-MMR in the same adults and (2) whether our methods capture the difference in MEG-MMR between native and nonnative speech contrasts in adults and (3) in older infants. Results from 18 adults with simultaneous M/EEG demonstrated a high correlation between the MEG-MMR and the EEG-MMR. Additionally, MEG-MMRs to native speech contrasts were different from ones to nonnative speech contrasts, replicating spatiotemporal patterns documented in the existing literature. Finally, we replicated this effect in the MEG-MMR in 14 infants aged between 9 and 14 months using the same methods. These findings validate our new methodologies with less than 15 mins of recording time for acquiring and analyzing speech-related MMRs across ages, paving the way for studying early language development, and improving early detection of language-related disorders.

Physical exercise acutely improves hippocampus-dependent memory. Whereas animal studies have offered cellular- and synaptic-level accounts of these effects, human neuroimaging studies show that exercise improves hippocampal-cortical connectivity at the macroscale level. However, the neurophysiological basis of exercise-induced effects on hippocampal-cortical circuits remains unknown. Experimental evidence supports the idea that hippocampal sharp wave-ripples (SWR) play a critical role in learning and memory. Coupling between SWRs in the hippocampus and neocortex may reflect modulations in inter-regional connectivity required by mnemonic processes. Here, we examine the hypothesis that exercise modulates hippocampal-cortical ripple dynamics in the human brain. We performed intracranial recordings in epilepsy patients undergoing pre-surgical evaluation, during awake resting state, before and after an exercise session. Exercise increased ripple rate in the hippocampus. Exercise also enhanced the coupling and phase-synchrony between cortical ripples in the limbic and the default mode (DM) cortical networks and hippocampal SWRs. Further, a higher heart rate during exercise, reflecting exercise intensity, was related to a subsequent increase in resting state ripples across specific cortical networks, including the DM network. These results offer the first direct evidence that a single exercise session elicits changes in ripple events, a well-established neurophysiological marker of mnemonic processing. The characterisation and anatomical distribution of the described modulation points to hippocampal ripples as a potential mechanism by which exercise elicits its reported short-term effects in cognition.

The non-rapid-eye movement (NREM) sleep power spectrum is composed of rhythmic and arrhythmic components, respectively associated with brain rhythms and scale-free dynamics. Both components are hypothesized to represent distinct processes underlying sleep-dependent memory consolidation as well as other brain complex processes. Recent advancements in spectral parametrization techniques and the use of multifractal models have enabled new insights into these components and their connection to brain networks. Aging impacts NREM sleep oscillations, but no animal studies considered the impact of age on rhythmic and arrhythmic components. In this study, we assessed the effects of age on the power spectrum and its two components using local field potential recordings in mice. We recorded across the cerebral cortex and within the hippocampus—a central brain hub involved in NREM sleep-dependent cognitive processing. Ten younger (7.6 months) and eleven older (15.7 months) C57BL/6 J male and female mice were continuously recorded over a 24-hour period. We extracted the NREM sleep standard and rhythmic spectra, controlled for scale-free activity, and estimated multifractal arrhythmic properties during NREM sleep using the Wavelet Leader and Bootstrap based MultiFractal analysis toolbox. Older mice showed specific alterations in both components compared to younger animals: reduced rhythmic gamma power in the anterior cortex, greater regional differentiation of scaling exponents, and higher multifractal dispersion of the arrhythmic component in the hippocampus. These findings demonstrate that aging alters rhythmic and arrhythmic properties of NREM sleep in distinct brain regions, suggesting that both contribute to age-related changes in sleep-dependent cognition.

Background: Electrical stimulation targeting the motor thalamus (Mthal) represents an emerging strategy for regulating motor cortical activity patterns, however the fundamental mechanisms and optimal stimulation configurations are not well established. Objective: To characterize how burst Mthal stimulation modulates cortical activity and to identify stimulation parameters that maximize cortical co-firing via thalamocortical rebound mechanisms. Methods: We conducted acute electrophysiological experiments in anesthetized rats using Mthal stimulation with systematically manipulated burst stimulation parameters (i.e., number of pulses and pulse width) in the low-frequency band (1-8 Hz) modulation cycle. Cortical responses across large areas covering primary and secondary motor cortex were recorded. Additionally, intracortical recordings were performed for detailed spike activity monitoring during stimulation. Cortical activity patterns in local field potentials and spike activity were analyzed to quantify the effects of Mthal stimulation on motor cortex. Computational thalamocortical circuit models were employed to explore the mechanistic basis of frequency-selective modulation effects. Results: Burst Mthal stimulation elicited tunable cortical excitation, with optimal modulation achieved at 3-4 Hz. This preferred frequency corresponded to the natural rebound timing of thalamocortical (TC) cells and generated maximal cortical co-firing and synchronization. Higher stimulation frequencies (e.g., 8 Hz) resulted in suppressed and diminished responses. Computational modeling further validated that the cellular mechanism of the TC cell rebound excitation leads to frequency-dependent cortical modulation. Conclusion: Burst Mthal stimulation demonstrates frequency-selective modulation of cortical network excitability, with 3-4 Hz protocols providing optimal enhancement of synchronized activity through exploitation of thalamocortical rebound dynamics. These results establish motor thalamic stimulation as a promising and efficient methodology for precise cortical network control and offer mechanistic foundations for developing therapeutic neuromodulation interventions aimed at motor system rehabilitation.

Transcranial Focused Ultrasound Stimulation (tFUS) is a promising non-invasive technique capable of modulating brain activity with high spatial precision. However, its efficacy for seizure suppression requires further exploration. This study aims to address whether tFUS of white matter can suppress seizures non-invasively. Repeated injections of a 4-Aminopyridine (4-AP) cocktail into the right somatosensory cortex (S1) induced cortical seizures in male rats under anesthesia with recording of both EEG and intracranial signals. Approximately one hour of tFUS was applied to the corpus callosum (CC) using a 128-element random-array transducer with 20 ms pulse duration, 1 Hz pulse repetition frequency, 2% duty cycle, and ~127 kPa pressure. Another 2-3 hours were used to assess post-stimulation effects. Seizure duration, seizure count, percent time in seizure, and inter-seizure interval were compared to a sham control for quantifying efficacy. The absolute frequency power, asymmetry index (AI), and phase lag index (PLI) were calculated to analyze brain activity changes induced by tFUS. CC tFUS can significantly reduce percent time in seizure, seizure duration, and seizure count, as well as increase inter-seizure interval. These effects extended up to 2 hours post-stimulation. We also observed a decrease in absolute power of the beta band and changes in the brain network, as evidenced by a decrease in synchronization and an improvement in interhemispheric balance. Our study is the first to show that white matter tFUS can significantly suppress seizures with a lasting post stimulation effect, potentially providing a safer alternative for drug-resistant epilepsy patients.

Large language models (LLMs) capture long-range contextual structure in natural language and have recently been shown to align with the human brain’s contextualized linguistic encoding. This makes them a promising computational probe for studying how context-dependent linguistic information is represented during natural speech perception. Speech perception often occurs in multi-talker environments, where attention must dynamically select among competing streams, yet how contextual information from attended and unattended speech is neurally encoded remains underexplored. Here, we investigate how auditory attention modulates neural tracking of context-dependent linguistic representations using electrocorticography (ECoG) and stereoelectroencephalography (sEEG) recordings from three epilepsy patients engaged in a two-conversation “cocktail party” paradigm. To model neural responses to attended and unattended speech streams, we used contextual word embeddings generated by large language models. We find that LLM-derived features reliably predict brain activity for the attended stream and that contextual information from the unattended stream also contributes to neural prediction. Importantly, these contributions extend beyond low-level acoustic features and shallow syntactic information, and depend on the surrounding linguistic context. Moreover, neural tracking of the unattended stream reflects shorter-range contextual integration than that of the attended stream. Together, these findings indicate that neural responses to speech reflect context-dependent linguistic representations from multiple concurrent speech streams, with attention modulating the depth and timescale of contextual integration. Our results highlight the utility of LLMs for probing higher-level linguistic representations in complex, naturalistic listening environments.

Selective activation of small versus large diameter nerve fibers represents a broad challenge in the electrical modulation of neural activity for clinical applications. For example, off-target activation of motor nerve fibers was implicated in several failed vagus nerve stimulation (VNS) clinical trials by effectively limiting maximum applicable current amplitudes, thereby preventing robust activation of smaller diameter fibers responsible for therapeutic effects. Kilohertz high-frequency (HF) block is one of several strategies proposed to overcome this gap, but has yet to be thoroughly investigated in large, multifascicular, mixed nerves comparable in scale to humans. Here, we evaluated effects of HF block on the neural, muscular, and cardiac responses evoked by traditional low-frequency (LF) VNS in a large animal (swine) model. We found that HF selectively blocks neural fibers, and their associated physiological responses, in a size dependent manner with a high degree of specificity and establish initial thresholds for achieving block in large multifascicular nerves. Critically, we demonstrate that appropriately titrating HF amplitude can eliminate off-target LF-evoked motor responses while preserving activation of smaller diameter fibers targeted by clinical VNS. Beyond VNS, these data establish HF as a potentially viable strategy in any neuromodulation therapies where off-target activation of large diameter fibers limits therapeutic efficacy.

The hippocampus is classically linked to memory, yet increasing evidence points to a broader role in perceptual inference and deviance detection. Predictive coding theories propose that perception minimizes mismatches between expected and actual sensory input, expressed in neural signatures such as mismatch negativity (MMN) and P300. Although MMN arises mainly from sensory and prefrontal cortices, the hippocampus is anatomically interconnected with both and may also contribute to prediction error processing. We recorded single- and multi-unit activity and local field potentials (LFPs) from DG and CA1 in urethane-anesthetized rats during an auditory oddball paradigm and a no-repetition control sequence to dissociate prediction error from repetition suppression. Approximately 20% of hippocampal neurons were sound responsive, and a subset showed deviant selectivity. Spiking activity predominantly reflected prediction errors, while LFPs revealed complementary contributions from repetition suppression and prediction error. Early LFP components were enhanced for randomly presented deviants, whereas later components within the P300 latency range were stronger for predictable deviants, indicating temporally distinct phases of error signaling and top-down modulation. These findings identify the hippocampus as an active contributor to auditory deviance detection and support a hierarchical model in which hippocampal circuits participate in predictive sensory processing beyond memory.

Understanding how the brain rapidly processes neural information through large-scale network dynamics is fundamental to neuroscience. Resting-state fMRI (rsfMRI) captures networks by probing spontaneous neural activity fluctuations, yet whether these networks can accommodate fast, sensitive information processing remains unknown. Here, we reveal brain-wide rsfMRI network dynamics (i.e., states and their transitions) that enable fast information processing through rapid activity-triggered network reconfiguration in male rats. Following activation of a single optogenetically evoked somatosensory thalamic input, states and transitions associated with internally-oriented information processing are quickly suppressed and diverted through basal forebrain and hypothalamus to strengthen externally-oriented (i.e., sensory) processes. Simultaneous rsfMRI and electrophysiology measurements in somatosensory and cingulate cortices demonstrate that intra-regional wide-band and inter-regional narrow-band (i.e., slow-oscillations) neural activity synchronizations directly drive rsfMRI network dynamics and reconfiguration to support fast processing of single thalamic input. Our study uncovers fast interactions between neural activity and rsfMRI networks in processing single neural input.

Stories, Chirps, And Noisy Sentences (MEG-SCANS) is a dataset that provides raw magnetoencephalography (MEG) recordings from 24 German-speaking subjects. Each subject listened to approximately one hour of stimuli, including two audiobooks, sentences from the Oldenburger Matrix Sentence Test (OLSA) for Speech Reception Threshold (SRT) assessment, and short up-chirps used to assess MEG signal quality. The dataset includes MEG data, structural MRI (Magnetic Resonance Imaging) scans of the head, corresponding audio material (audiobooks, OLSA envelopes, and chirp stimuli), and behavioral audiogram and SRT results from hearing screenings. Organized according to the Brain Imaging Data Structure (BIDS), this resource offers a robust benchmark for large-scale encoding/decoding analyses of temporally-resolved brain responses to speech. Comprehensive Matlab and Python code are included to replicate key data validations, ensuring transparency and reproducibility.