Biology subjects

Keil, A.

Publications and source records attributed to Keil, A..

34 records · Page 2Linked to original sources

bioRxiv2024

Decoding in the fourth dimension: Classification of temporal patterns and their generalization across locations

Neuroscience research has increasingly used decoding techniques, in which multivariate statistical methods identify patterns in neural data that allow the classification of experimental conditions or participant groups. Typically, the features used for decoding are spatial in nature, including voxel patterns and electrode locations. However, the strength of many neurophysiological recording techniques such as electroencephalography or magnetoencephalography is in their rich temporal, rather than spatial, content. The present report proposes a new decoding method that relies on the time information contained in neural time series. This information is then used in a subsequent step, generalization across location (GAL), which characterizes the relationship between sensor locations based on their ability to cross-decode. Two datasets are used to demonstrate usage of this method, referred to as time-GAL, involving (1) event-related potentials in response to affective pictures and (2) steady-state visual evoked potentials in response to aversively conditioned grating stimuli. In both cases, experimental conditions were successfully decoded based on the temporal features contained in the neural time series. Cross-decoding occurred in regions known to be involved in visual and affective processing. We conclude that the time-GAL approach holds promise for analyzing neural time series from a wide range of paradigms and measurement domains providing an assumption-free method to quantifying differences in temporal patterns of neural information processing and whether these patterns are shared across sensor locations. Author summaryDecoding and classification approaches are widely used in computational biology. In the field of neuroscience, pattern classification approaches typically use spatial information. In many instances, neural time series however are best defined by the their temporal, rather than spatial, features. Here, we propose a novel decoding approach taking advantage of the temporal information. Specifically, we utilize the waveform of neural time series as features for decoding experimental conditions and quantify each decoders generalization across locations (GAL) in multi-channel recordings. We illustrate the usage of our open source toolbox using two datasets, showing the sensitivity of the method to systematic condition differences in temporal dynamics along with its ability to capture and quantify spatial dependencies between recording locations.

neuroscience↗

bioRxiv2024

Quantifying Population-level Neural Tuning Functions Using Ricker Wavelets and the Bayesian Bootstrap

Experience changes the tuning of sensory neurons, including neurons in retinotopic visual cortex, as evident from work in humans and non-human animals. In human observers, visuo-cortical re-tuning has been studied during aversive generalization learning paradigms, in which the similarity of generalization stimuli (GSs) with a conditioned threat cue (CS+) is used to quantify tuning functions. This work utilized pre-defined tuning shapes reflecting prototypical generalization (Gaussian) and sharpening (Difference-of-Gaussians) patterns. This approach may constrain the ways in which re-tuning can be characterized, for example if tuning patterns do not match the prototypical functions or represent a mixture of functions. The present study proposes a flexible and data-driven method for precisely quantifying changes in neural tuning based on the Ricker wavelet function and the Bayesian bootstrap. The method is illustrated using data from a study in which university students (n = 31) performed an aversive generalization learning task. Oriented gray-scale gratings served as CS+ and GSs and a white noise served as the unconditioned stimulus (US). Acquisition and extinction of the aversive contingencies were examined, while steady-state visual event potentials (ssVEP) and alpha-band (8-13 Hz) power were measured from scalp EEG. Results showed that the Ricker wavelet model fitted the ssVEP and alpha-band data well. The pattern of re-tuning in ssVEP amplitude across the stimulus gradient resembled a generalization (Gaussian) shape in acquisition and a sharpening (Difference-of-Gaussian) shape in an extinction phase. As expected, the pattern of re-tuning in alpha-power took the form of a generalization shape in both phases. The Ricker-based approach led to greater Bayes factors and more interpretable results compared to prototypical tuning models. The results highlight the promise of the current method for capturing the precise nature of visuo-cortical tuning functions, unconstrained by the exact implementation of prototypical a-priori models. HighlightsO_LITuning functions are a common way for describing sensory responses, primarily in the visual cortex. C_LIO_LIThe quantification and interpretation of tuning functions has faced computational and conceptual problems. C_LIO_LIWe demonstrated how the Ricker function can be used as a simple and interpretable way for measuring tuning functions. C_LIO_LIWe applied a Ricker function together with a Bayesian Bootstrap approach across a gradient of stimulus features in a generalization conditioning task to characterize visual tuning in the human EEG data. C_LI

neuroscience↗

bioRxiv2024

Neurophysiological and Autonomic Dynamics of Threat Processing During Sustained Social Fear Generalization

Survival in dynamic environments requires that organisms learn to predict danger from situational cues. One key facet of threat prediction is generalization from a predictive cue to similar cues, ensuring that a cue-outcome contingency is applied beyond the original learning environment. Generalization has been observed in laboratory studies of aversive conditioning: behavioral and physiological processes generalize responses from a stimulus paired with threat (the CS+) to unpaired stimuli, with response magnitudes varying with CS+ similarity. In contrast, work focusing on sensory responses in visual cortex has found a sharpening pattern, in which responses to stimuli closely resembling the CS+ are maximally suppressed, potentially reflecting lateral inhibitory interactions with the CS+ representation. Originally demonstrated with simple visual cues, changes in visuocortical tuning have also been observed in threat generalization learning across facial identities. It is unclear to what extent these visuocortical changes represent transient or sustained effects and if generalization learning requires prior conditioning to the CS+. The present study addressed these questions using EEG and pupillometry in an aversive generalization paradigm involving hundreds of trials using a gradient of facial identities. Visuocortical ssVEP sharpening occurred after dozens of trials of generalization learning without prior differential conditioning, but diminished as learning continued. By contrast, generalization of alpha power suppression, pupil dilation, and self-reported valence and arousal was seen throughout the experiment. Findings are consistent with threat processing models emphasizing the role of changing visucocortical and attentional dynamics when forming, curating, and shaping fear memories as observers continue learning about stimulus-outcome contingencies.

neuroscience↗

bioRxiv2023

Auditory Aversive Generalization Learning Prompts Threat-Specific Changes in Alpha-Band Activity

Pairing a neutral stimulus with aversive outcomes prompts neurophysiological and autonomic changes in response to the conditioned stimulus (CS+), compared to cues that signal safety (CS-). One of these changes--selective amplitude reduction of parietal alpha-band oscillations-- has been reliably linked to processing of visual CS+. It is however unclear to what extent auditory conditioned cues prompt similar changes, how these changes evolve as learning progresses, and how alpha reduction in the auditory domain generalizes to similar stimuli. To address these questions, fifty-five participants listened to three sine wave tones, with either the highest or lowest pitch (CS+) being associated with a noxious white noise burst. A threat specific (CS+) reduction in occipital-parietal alpha-band power was observed similar to changes expected for visual stimuli. No evidence for aversive generalization to the tone most similar to the CS+ was observed in terms of alpha-band power changes, aversiveness ratings, or pupil dilation. By-trial analyses found that selective alpha-band changes continued to increase as aversive conditioning continued, beyond when participants reported awareness of the contingencies. The results support a theoretical model in which selective alpha power represents a cross-modal index of continuous aversive learning, accompanied by sustained sensory discrimination of conditioned threat from safety cues.

physiology↗

bioRxiv2023

Overexpression of mitochondrial fusion genes enhances resilience and extends longevity

The dynamicity of the mitochondrial network is crucial for meeting the ever-changing metabolic and energy needs of the cell. Mitochondrial fission promotes the degradation and distribution of mitochondria, while mitochondrial fusion maintains mitochondrial function through the complementation of mitochondrial components. Previously, we have reported that mitochondrial networks are tubular, interconnected and well-organized in young, healthy C. elegans, but become fragmented and disorganized with advancing age and in models of age-associated neurodegenerative disease. In this work, we examine the effects of increasing mitochondrial fission or mitochondrial fusion capacity by ubiquitously overexpressing the mitochondrial fission gene drp-1 or the mitochondrial fusion genes fzo-1 and eat-3, individually or in combination. We then measured mitochondrial function, mitochondrial network morphology, physiologic rates, stress resistance and lifespan. Surprisingly, we found that overexpression of either mitochondrial fission or fusion machinery both resulted in an increase in mitochondrial fragmentation. Similarly, both mitochondrial fission and mitochondrial fusion overexpression strains have extended lifespans and increased stress resistance, which appears to be at least partially due to the upregulation of multiple stress response pathways in these strains. Overall, our work demonstrates that increasing the expression of mitochondrial fission or fusion genes extends lifespan and improves biological resilience without promoting the maintenance of a youthful mitochondrial network morphology. This work highlights the importance of the mitochondria for both resilience and longevity.

developmental biology↗

bioRxiv2023

Attentional Engagement and Disengagement: Quantifying Attentional Shifts Utilizing the Steady State Visual Evoked Potentials

A large body of ssVEP research has provided significant insights into the temporal dynamics of attentional processes. While these studies focused primarily on group level inspection, there is a need for further research employing methodological approaches that enable the examination of individual-level variability. This is particularly relevant in psychological contexts, where such measures are linked to various cognitive and clinical outcomes. In the present study, we aimed to measure and discern attentional shift processes, examining both group and individual subject dynamics. We utilized EEG frequency tagging to examine attentional engagement, disengagement, and reengagement while participants switched focus between four flickering stimuli. Analysis of ssVEPs revealed significant changes in amplitude between attentional conditions. Specifically, group-level results indicated an increase in activity during engagement with the first target, followed by a decrease upon disengagement, while reengagement with the second target showed a corresponding increase in activity occurring on average 110 ms prior to disengagement. Distinct individual patterns emerged, with participants showing either disengagement, reengagement, both, or no shifts. Notably, the timing and order of these attentional shifts varied considerably across individuals relative to target switch events. These findings demonstrate the ability of this approach to quantify attentional shifts on both group and individual levels, providing a foundation for further research into individual differences in attentional control, which may have implications for understanding adaptive and maladaptive psychological functioning. HighlightsO_LIEEG frequency tagging captures attentional engagement, disengagement, and reengagement processes. C_LIO_LIGroup-level ssVEP analysis reveals that attentional reengagement occurs 110 ms before attentional disengagement. C_LIO_LIIndividual-level analysis demonstrates diverse patterns of attentional shift timing and order. C_LIO_LIThe experimental framework successfully quantifies attentional dynamics on the group and individual levels. C_LI

neuroscience↗

bioRxiv2022

Effects of Neurofeedback training on performance in laboratory tasks: A systematic review

Neurofeedback procedures are attracting increasing attention in the neuroscience community. Based on the principle that participants, through suitable feedback, may learn to affect specific aspects of their brain activity, neurofeedback has been applied to basic research, translational, and clinical science alike. A large segment of the extant empirical research as well as review articles have focused on the extent to which neurofeedback interventions affect mental health outcomes, cognitive capacity, aging, and other complex behaviors. Another segment has aimed to characterize the extent to which neurofeedback affects the targeted neural processes. At this time, there is no current systematic review of the effects of neurofeedback on healthy participants performance in experimental tasks. Such a review is relevant in this rapidly evolving field because changes in experimental task performance are traditionally considered a hallmark of changing neurocognitive processes, often established in neurotypical individuals. This systematic review addresses this gap in the literature using the PRISMA method, building on earlier reviews on the same topic. Empirical studies using EEG or fMRI to alter brain processes linked to established, well-defined cognitive and affective laboratory tasks were reviewed. Substantial variability was found regarding the nature of the control for placebo effects, the implementation of the feedback, and the neural targets of feedback. Importantly, only a minority of the studies reported statistically meaningful effects of neurofeedback on performance in cognitive and affective tasks. Examining effect sizes and p-values in a subset of studies found no evidence for reporting bias, while also not finding systematic relations between study characteristics such as sample size or experimental control on the one hand and efficacy on the other. Implications for future work are discussed.

neuroscience↗

bioRxiv2022

Effects of Aversive Classical Conditioning on Pupil Dilation and Microsaccades

Unintentional shifts of gaze and the modulation of pupil size are both highly automated processes that serve to regulate the initial influx of visual information. The present work investigated these mechanisms as they came to differentially respond to initially unthreatening stimuli following aversive conditioning. The classical conditioning experimental paradigm employed simple grating stimuli (Gabor patches) shown individually at various (5) on-screen locations, one of which was paired with a noxious auditory unconditioned stimulus (US). Aversively paired Gabor patches elicited an attenuated initial constriction of the pupil (pupillary light response; PLR) along with more rapid re-dilation compared to otherwise identical but unpaired gratings. Modulation of both the PLR and the rate of re-dilation following conditioning showed pronounced individual differences. Rapid eye movements away from fixation (microsaccades) were suppressed for the aversively associated compared to unassociated stimulus locations at several post-stimulus latencies. Mutual information between pupil dilation and microsaccade rate, meanwhile, did not differ between the aversively associated and unassociated visual on-screen locations. Together, these results suggest that measures of pupil diameter and microsaccade rate supply complementary information on early-stage processes of associative learning through experience.

neuroscience↗

bioRxiv2022

Decoding the temporal dynamics of affective scene processing

Natural images containing affective scenes are used extensively to investigate the neural mechanisms of visual emotion processing. Functional fMRI studies have shown that these images activate a large-scale distributed brain network that encompasses areas in visual, temporal, and frontal cortices. The underlying spatial and temporal dynamics among these network structures, however, remain to be characterized. We recorded simultaneous EEG-fMRI data while participants passively viewed affective images from the International Affective Picture System (IAPS). Applying multivariate pattern analysis to decode EEG data, and representational similarity analysis to fuse EEG data with simultaneously recorded fMRI data, we found that: (1) ~100 ms after picture onset, perceptual processing of complex visual scenes began in early visual cortex, proceeding to ventral visual cortex at ~160 ms, (2) between ~200 and ~300 ms (pleasant pictures: ~200 ms; unpleasant pictures: ~260 ms), affect-specific neural representations began to form, supported mainly by areas in occipital and temporal cortices, and (3) affect-specific neural representations, lasting up to ~2 s, were stable and exhibited temporally generalizable activity patterns. These results suggest that affective scene representations in the brain are formed in a valence-dependent manner and are sustained by recurrent neural interactions among distributed brain areas.

neuroscience↗

bioRxiv2021

Oscillatory brain activity links experience to expectancy during associative learning

Associating a novel situation with a specific outcome involves a cascade of cognitive processes, including selecting relevant stimuli, forming predictions regarding expected outcomes, and updating memorized predictions based on experience. The present manuscript uses computational modeling and machine learning to test the hypothesis that alpha-band (8-12 Hz) neural oscillations are involved in the updating of expectations based on experience. Participants learned that a visual cue predicted an aversive loud noise with a probability of 50 percent. The Rescorla-Wagner model of associative learning explained trial-wise changes in self-reported noise expectancy as well as alpha power changes. Both experience in the past trial and self-reported expectancy for the subsequent trial were accurately decoded based on the topographical distribution of alpha power. Decodable information during initial association formation and contingency report recurred when viewing the conditioned cue. Findings support the idea that alpha oscillations have multiple, simultaneous, and unique roles in association formation.

neuroscience↗

bioRxiv2020

Aversive Conditioning of Spatial Position Sharpens Neural Population-level Tuning in VisualCortex and Selectively Reduces Alpha-band Activity

Processing capabilities for many low-level visual features are experientially malleable, aiding sighted organisms in adapting to dynamic environments. Explicit instructions to attend a specific visual field location influence retinotopic visuocortical activity, amplifying responses to stimuli appearing at cued spatial positions. It remains undetermined, however, both how such prioritization affects surrounding non-prioritized locations, and if a given retinotopic spatial position can attain enhanced cortical representation through experience rather than instruction. This work examined visuocortical response changes as human observers learned, through differential classical conditioning, to associate specific on-screen locations with aversive outcomes. Using dense-array EEG and pupillometry, we tested the pre-registered hypotheses of either sharpening or generalization around an aversively associated location following a single conditioning session. Specifically, competing hypotheses tested if mean response changes would take the form of a gaussian (generalization) or difference-of-gaussian (sharpening) distribution over spatial positions, peaking at the viewing location paired with a noxious noise. Occipital 15 Hz steady-state visual evoked potential (ssVEP) responses were selectively heightened when viewing aversively paired locations and displayed a non-linear, difference-of-gaussian profile across neighboring locations, consistent with suppressive surround modulation of non-prioritized positions. Measures of alpha band (8 - 12.8 Hz) activity and pupil diameter also exhibited selectively heightened responses to noise-paired locations but did not evince any difference across the non-paired locations. These results indicate that visuocortical spatial representations are sharpened in response to location-specific aversive conditioning, while top-down influences indexed by alpha power reduction exhibit all-or-none modulation. Significance StatementIt is increasingly recognized that early visual cortex is not a static processor of physical features, but is instead constantly shaped by perceptual experience. It remains unclear, however, to what extent the cortical representation of many fundamental features, including visual field location, is malleable by experience. Using EEG and an aversive classical conditioning paradigm, we observed sharpening of visuocortical responses to stimuli appearing at aversively associated locations along with location-selective facilitation of response systems indexed by pupil diameter and EEG alpha power. These findings highlight the experience-dependent flexibility of retinotopic spatial representations in visual cortex, opening avenues towards novel treatment targets in disorders of attention and spatial cognition.

neuroscience↗

bioRxiv2020

Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex

Repeated exposure to threatening stimuli alters sensory responses. We investigated the underlying neural mechanism by recording simultaneous EEG-fMRI from human participants viewing oriented gratings during Pavlovian fear conditioning. In acquisition, one grating (the CS+) was paired with a noxious noise, the unconditioned stimulus (US). The other grating (CS-) was never paired with US. In habituation, which preceded acquisition, and in final extinction, the same two gratings were presented without the US. Using fMRI-BOLD multivoxel patterns in primary visual cortex during habituation as reference, we found that during acquisition, aversive learning selectively prompted systematic changes in multivoxel patterns evoked by the CS+. Specifically, CS+ evoked voxel patterns in V1 became sparser as aversive learning progressed, and the sparse pattern was preserved in extinction. Concomitant with the voxel pattern changes, occipital alpha oscillations were increasingly more desynchronized during CS+ (but not CS-) trials. Across acquisition trials, the rate of change in CS+-related alpha desynchronization was correlated with the rate of change in multivoxel pattern representations of the CS+. Furthermore, alpha oscillations co-varied with BOLD in the right temporal-parietal junction, but not with BOLD in the amygdala. Thus, fear conditioning prompts persistent sparsification of threat cue representations, likely mediated by attention-related mechanisms.

neuroscience↗

bioRxiv2019

Extinction-resistant attention to long-term conditioned threat is indexed by selective visuocortical alpha suppression in humans

While ERP studies have shown heightened early visual attention to conditioned threat, it is unknown whether this attentional prioritization is sustained throughout later processing stages and whether it is robust to extinction. To investigate sustained visual attention, we assessed visuocortical alpha suppression in response to conditioned and extinguished threat. N = 87 participants underwent a two-day threat conditioning paradigm with acquisition and extinction on one day and a critical recall test one day later. EEG time-frequency analyses revealed that, on Day 2, threat-conditioned vs. safety cues evoked stronger occipital alpha power suppression from 600 to 1200 ms. Notably, this suppression was resistant to extinction. The present study showed for the first time that threat conditioning enhances sustained modulation of visuocortical attention to threat in the long term. The long-term stability and extinction resistance of alpha suppression suggests a crucial role of visuocortical attention mechanisms in the maintenance of learned fears.

neuroscience↗

bioRxiv2018

Decreased Inter Trial Phase Coherence of Steady-State Visual Evoked Responses in Sleep Deprivation

1.Sleep loss has detrimental effects on cognitive and emotional functioning. These impairments have been associated with alterations in EEG measures of power spectrum and event-related potentials, however the impact of sleep loss on inter trial phase coherence (ITPC), a measure of phase consistency over experimental trials, remains mostly unknown. ITPC is thought to reflect the ability of the neural response to temporally synchronize with relevant events, thus optimizing information processing.\n\nIn the current study we investigated the effects of sleep deprivation on information processing by evaluating the phase consistency of steady-state visual evoked potentials (ssVEPs) as well as amplitude-based measures of ssVEP, obtained from a group of 18 healthy individuals following 24 hours of total sleep deprivation and after a night of habitual sleep. An ssVEP task was utilized, which included the presentation of dots flickering at 7.5 Hz, along with a cognitive-emotional task. Our results show that ITPC is significantly reduced under sleep deprivation relative to habitual sleep. Interestingly, decreased ITPC under sleep deprivation was associated with decreased behavioral performance in the psychomotor vigilance task (PVT), a validate measure of reduced vigilance following lack of sleep.\n\nThe results suggest that the capability of the brain to synchronize with rhythmic stimuli is disrupted without sleep. Thus, decreased ITPC may represent an objective and mechanistic measure of sleep loss, allowing future work to study the relation between brain-world synchrony and the specific functional impairments associated with sleep deprivation.

neuroscience↗

bioRxiv2018

Attention to a threat-related feature does not interfere with concurrent attentive feature selection

Visual features that are associated with a task and those that predict noxious events both prompt selectively heightened visuocortical responses. Conflicting views exist regarding how the competition between a task-related and a threat-related feature is resolved when they co-occur in time and space. Utilizing aversive differential Pavlovian conditioning, we investigated the visuocortical representation of two simultaneously presented, fully overlapping visual stimuli. Stimuli were isoluminant red and green random dot kinematograms (RDKs) which flickered at two tagging frequencies (8.57 Hz, 12 Hz) to elicit distinguishable steady-state visual evoked potentials (ssVEPs). Occasional coherent motion events prompted a motor response or predicted a noxious noise. These events occurred either in the green (task cue), the red (threat cue), or in both RDKs simultaneously. In an initial habituation phase, participants responded to coherent motion of the green RDK with a key press, but no loud noise was presented at any time. Here, selective amplification was seen for the task-relevant (green) RDK, but interference was observed when both RDKs simultaneously showed coherent motion. Upon pairing the threat cue with the noxious noise in the subsequent acquisition phase, the threat cue-evoked ssVEP (red RDK) was also amplified, but this amplification did not interact with amplification of the task cue, and did not alter the behavioral or visuocortical interference effect seen during simultaneous coherent motion. Results demonstrate that although competing feature conjunctions result in interference in visual cortex, the acquisition of a bias towards an individual threat-related feature does not result in additional cost effects.

neuroscience↗

bioRxiv2018

Improving preterm newborn identification in low-resource settings with machine learning

BackgroundGlobally, preterm birth is the leading cause of neonatal death with estimated prevalence and associated mortality highest in low- and middle-income countries (LMICs). Accurate identification of preterm infants is important at the individual level for appropriate clinical intervention as well as at the population level for informed policy decisions and resource allocation. As early prenatal ultrasound is commonly not available in these settings, gestational age (GA) is often estimated using newborn assessment at birth. This approach assumes last menstrual period to be unreliable and birthweight to be unable to distinguish preterm infants from those that are small for gestational age (SGA). We sought to leverage machine learning algorithms incorporating maternal factors associated with SGA to improve accuracy of preterm newborn identification in LMIC settings.\n\nMethods and FindingsThis study uses data from an ongoing obstetrical cohort in Lusaka, Zambia that uses early pregnancy ultrasound to estimate GA. Our intent was to identify the best set of parameters commonly available at delivery to correctly categorize births as either preterm (<37 weeks) or term, compared to GA assigned by early ultrasound as the gold standard. Trained midwives conducted a newborn assessment (<72 hours) and collected maternal and neonatal data at the time of delivery or shortly thereafter. New Ballard Score (NBS), last menstrual period (LMP), and birth weight were used individually to assign GA at delivery and categorize each birth as either preterm or term. Additionally, machine learning techniques incorporated combinations of these measures with several maternal and newborn characteristics associated with prematurity and SGA to develop GA at delivery and preterm birth prediction models. The distribution and accuracy of all models were compared to early ultrasound dating. Within our live-born cohort to date (n = 862), the median GA at delivery by early ultrasound was 39.4 weeks (IQR: 38.3 - 40.3). Among assessed newborns with complete data included in this analysis (n = 458), the median GA by ultrasound was 39.6 weeks (IQR: 38.4 - 40.3). Using machine learning, we identified a combination of six accessible parameters (LMP, birth weight, twin delivery, maternal height, hypertension in labor, and HIV serostatus) that can be used by machine learning to outperform current GA prediction methods. For preterm birth prediction, this combination of covariates correctly classified >94% of newborns and achieved an area under the curve (AUC) of 0.9796.\n\nConclusionsWe identified a parsimonious list of variables that can be used by machine learning approaches to improve accuracy of preterm newborn identification. Our best performing model included LMP, birth weight, twin delivery, HIV serostatus, and maternal factors associated with SGA. These variables are all easily collected at delivery, reducing the skill and time required by the frontline health worker to assess GA.

bioinformatics↗