Biology subjects

Knight, R. T.

Publications and source records attributed to Knight, R. T..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Physical Exercise Improves Working Memory through Ripple-Spindle Coupling

Spindle-ripple coupling enhances memory consolidation during sleep. Ripples, representing the compressed reactivation of environmental information, provide a mechanism for retaining memory information in chronological order and are also crucial for working memory (WM) during wakefulness. Brief sessions of physical exercise (PE) are proposed to boost WM. In concurrent EEG/MEG sessions, we investigated the role of PE in WM performance and high-frequency-ripple to spindle coupling. Ripples, identified in MEG sensors covering the medial temporal lobe (MTL) region, predicted individual WM performance. Ripples were locked to robust oscillatory patterns in the EEG defined spindle band. Spindle activity and ripples decrease during initial stimulus presentation and rebound after 1 sec. Behaviorally, PE enhanced WM performance. Neurophysiologically, PE scaled the ripple rate with the number of items to be kept in WM and strengthened the coupling between ripple events and spindle oscillations. These findings reveal that PE enhances WM by coordinating ripple-spindle interaction.

neuroscience↗

bioRxiv2023

Ventrointermediate thalamic stimulation improves motor learning in humans

Ventrointermediate thalamic stimulation (VIM-DBS) modulates oscillatory activity in a cortical network including primary motor cortex, premotor cortex, and parietal cortex. Here we show that, beyond the beneficial effects of VIM-DBS on motor execution, this form of invasive stimulation facilitates production of sequential finger movements that follow a fixed sequence but not when the sequence is selected at random. These results highlight the role of thalamo-cortical activity in motor learning.

neuroscience↗

bioRxiv2023

Differential neural mechanisms underlie cortical gating of visual spatial attention mediated by alpha-band oscillations

Selective attention relies on neural mechanisms that facilitate processing of behaviorally relevant sensory information while suppressing irrelevant information, consistently linked to alpha-band oscillations in human M/EEG studies. We analyzed cortical alpha responses from intracranial electrodes implanted in eight epilepsy patients, who performed a visual spatial attention task. Electrocorticographic data revealed a spatiotemporal dissociation between attention-modulated alpha desynchronization, associated with the enhancement of sensory processing, and alpha synchronization, associated with the suppression of sensory processing, during the cue-target interval. Dorsal intraparietal areas contralateral to the attended hemifield primarily exhibited a delayed and sustained alpha desynchronization, while ventrolateral extrastriatal areas ipsilateral to the attended hemifield primarily exhibited an earlier and sustained alpha synchronization. Analyses of cross-frequency coupling between alpha phase and broadband high-frequency activity (HFA) further revealed cross-frequency interactions along the visual hierarchy contralateral to the attended locations. Directionality analyses indicate that alpha phase in early and extrastriatal visual areas modulated HFA power in downstream visual areas, thus potentially facilitating the feedforward processing of an upcoming, spatially predictable target. In contrast, in areas ipsilateral to the attended locations, HFA power modulated local alpha phase in early and extrastriatal visual areas, with suppressed interareal interactions, potentially attenuating the processing of distractors. Our findings reveal divergent alpha-mediated neural mechanisms underlying target enhancement and distractor suppression during the deployment of spatial attention, reflecting enhanced functional connectivity at attended locations, while suppressed functional connectivity at unattended locations. The collective dynamics of these alpha-mediated neural mechanisms play complementary roles in the efficient gating of sensory information. SIGNIFICANCE STATEMENTSelective attention relies on neural mechanisms involved in target enhancement and distractor suppression to guide behavior. Using electrocorticographic data in humans, we show a spatiotemporal dissociation between cortical activities engaged in target facilitation and distractor inhibition during attentional deployment. We also found that, at attended locations, interareal interactions are enhanced through cross-frequency coupling along the visual hierarchy to potentially facilitate the processing of a spatially predictable target. In contrast, at unattended locations, intraareal interactions are enhanced through cross-frequency coupling, and interareal interactions are suppressed, together to potentially attenuate the processing of distractors. Our findings reveal that such a distributed cortical organization and complementary neural mechanisms enable efficient gating and filtering of sensory information in the anticipatory processing of spatial attention.

neuroscience↗

bioRxiv2023

Decoding reveals the neural representation of held and manipulate musical thoughts

Vividly imagining a song or a melody is a skill that many people accomplish with relatively little effort. However, we are only beginning to understand how the brain represents, holds, and manipulates these musical "thoughts". Here, we decoded perceived and imagined melodies from magnetoencephalography (MEG) brain data (N = 71) to characterize their neural representation. We found that, during perception, auditory regions represent the sensory properties of individual sounds. In contrast, a widespread network including fronto-parietal cortex, hippocampus, basal nuclei, and sensorimotor regions hold the melody as an abstract unit during both perception and imagination. Furthermore, the mental manipulation of a melody systematically changes its neural representation, reflecting volitional control of auditory images. Our work sheds light on the nature and dynamics of auditory representations, informing future research on neural decoding of auditory imagination.

neuroscience↗

bioRxiv2023

Differential Contribution of Sensorimotor Cortex and Subthalamic Nucleus to Unimanual and Bimanual Hand Movements

Why does unilateral subthalamic nucleus deep brain stimulation improve motor function bilaterally? To address this clinical observation, we collected parallel neural recordings from sensorimotor cortex and the subthalamic nucleus during repetitive ipsilateral, contralateral, and bilateral hand movements in patients with Parkinsons disease undergoing subthalamic nucleus deep brain stimulation. We used a cross-validated electrode-wise encoding model to map EMG data to the neural signals. Electrodes in the subthalamic nucleus encoded movement in a comparable manner for both hands during unimanual and bimanual movements, whereas sensorimotor cortex electrodes displayed a strong contralateral bias. To examine representational overlap in encoding across the two hands, we trained the model with data from one condition (contralateral hand) and used the trained weights to predict neural activity for movements produced with the other hand (ipsilateral hand). Overall, between-hand generalization was poor and this limitation was evident in both SMC and STN. A similar method was used to probe representational overlap across different task contexts (unimanual vs. bimanual). Task context was more important for the STN compared to the SMC indicating that neural activity in the STN showed greater divergence between the unimanual and bimanual conditions. These results indicate that whereas SMC activity is strongly lateralized and relatively context-free, STN integrates contextual information with the ongoing behavior. Significance StatementUnilateral subthalamic nucleus deep brain stimulation (DBS) improves both contralateral and ipsilateral motor symptoms of Parkinsons disease. To explore mechanisms for bilateral improvement, parallel neural recordings from the sensorimotor cortex (SMC) and subthalamic nucleus (STN) were recorded in patients with Parkinsons disease undergoing DBS. Neural activity and muscle activity from the hands were collected while patients performed unimanual and bimanual repetitive hand movements. Activity in SMC primarily encoded contralateral movements and was relatively context-free. In contrast, STN encoded movements in a comparable manner for both hands and was sensitive to the behavioral context.

neuroscience↗

bioRxiv2023

Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods

Precise electrode localization is important for maximizing the utility of intracranial EEG data. Electrodes are typically localized from post-implantation CT artifacts, but algorithms can fail due to low signal-to-noise ratio, unrelated artifacts, or high-density electrode arrays. Minimizing these errors usually requires time-consuming visual localization and can still result in inaccurate localizations. In addition, surgical implantation of grids and strips typically introduces non-linear brain deformations, which result in anatomical registration errors when post-implantation CT images are fused with the pre-implantation MRI images. Several projection methods are currently available, but they either fail to produce smooth solutions or do not account for brain deformations. To address these shortcomings, we propose two novel algorithms for the anatomical registration of intracranial electrodes that are almost fully automatic and provide highly accurate results. We first present GridFit, an algorithm that simultaneously localizes all contacts in grids, strips, or depth arrays by fitting flexible models to the electrodes CT artifacts. We observed localization errors of less than one millimeter (below 8% relative to the inter-electrode distance) and robust performance under the presence of noise, unrelated artifacts, and high-density implants when we ran [~]6000 simulated scenarios. Furthermore, we validated the method with real data from 20 intracranial patients. As a second registration step, we introduce CEPA, a brain-shift compensation algorithm that combines orthogonal-based projections, spring-mesh models, and spatial regularization constraints. When tested with real data from 15 patients, anatomical registration errors were smaller than those obtained for well-established alternatives. Additionally, CEPA accounted simultaneously for simple mechanical deformation principles, which is not possible with other available methods. Inter-electrode distances of projected coordinates smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. Moreover, in an additional validation procedure, we found that modeling resting-state high-frequency activity (75-145 Hz) in five patients further supported our new algorithm. Together, GridFit and CEPA constitute a versatile set of tools for the registration of subdural grid, strip, and depth electrode coordinates that provide highly accurate results even in the most challenging implantation scenarios. The methods presented here are implemented in the iElectrodes open-source toolbox, making their use simple, accessible, and straightforward to integrate with other popular toolboxes used for analyzing electrophysiological data.

bioinformatics↗

bioRxiv2023

Dynamic expectations: Behavioral and electrophysiological evidence of sub-second updates in reward predictions

Expectations are often dynamic: any sports fan knows that expectations are rapidly updated as games unfold. Yet expectations have traditionally been studied as static. Here, using slot machines as a case study, we provide parallel behavioral and electrophysiological evidence of sub-second moment-to-moment changes in expectations. In Study 1, we show that the dynamics of the EEG signal before the slot machine stopped differed depending on the nature of the outcome, including not only whether the participant won or lost, but also how close they came to winning. In line with our predictions, Near Win Before outcomes (the slot machine stops one item before a match) were similar to Wins, but different than Near Win After (the machine stops one item after a match) and Full Miss (the machine stops two or three items from a match). In Study 2, we designed a novel behavioral paradigm to measure moment-to-moment changes in expectations via dynamic betting. We found that different outcomes also elicited unique expectation trajectories in the deceleration phase. Notably, these behavioral expectation trajectories paralleled Study 1s EEG activity in the last second prior to the machines stop. In Studies 3 (EEG) and 4 (behavior) we replicated these findings in the loss domain where a match entails a loss. Again, we found a significant correlation between behavioral and EEG results. These four studies provide the first evidence that dynamic sub-second updates in expectations can be behaviorally and electrophysiologically measured. Our findings open up new avenues for studying the ongoing dynamics of reward expectations and their role in healthy and unhealthy cognition.

neuroscience↗

bioRxiv2023

Comparing rapid rule-learning strategies in humans and monkeys

Inter-species comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of macaque monkey and human strategies on an analogue of the Wisconsin Card Sort Test, a widely studied and applied multi-attribute measure of cognitive function, wherein performance requires the inference of a changing rule given ambiguous feedback. We found that well-trained monkeys rapidly infer rules but are three times slower than humans. Model fits to their choices revealed hidden states akin to feature-based attention in both species, and decision processes that resembled a Win-stay lose-shift strategy with key differences. Monkeys and humans test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidates. An attention-set based learning stage categorization revealed that perseveration, random exploration and poor sensitivity to negative feedback explain the under-performance in monkeys.

animal behavior and cognition↗

bioRxiv2023

Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex

Orbitofrontal cortex (OFC) is classically linked to inhibitory control, emotion regulation and reward processing. Recent perspectives propose that the OFC also generates predictions about perceptual events, actions, and their outcomes. We tested the role of the OFC in detecting violations of prediction at two levels of abstraction (i.e., hierarchical predictive processing) by studying the event-related potentials (ERPs) of patients with focal OFC lesions (n = 12) and healthy controls (n = 14) while they detected deviant sequences of tones in a Local-Global paradigm. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and at a global (i.e., between sequences) level. In OFC patients, ERPs elicited by standard tones were unaffected at both local and global levels compared to controls. However, patients showed an attenuated mismatch negativity (MMN) and P3a to local prediction violation, as well as a diminished MMN followed by a delayed P3a to the combined local and global level prediction violation. The subsequent P3b component to conditions involving violations of prediction at the level of global rules was preserved in the OFC group. Comparable effects were absent in patients with lesions restricted to the lateral PFC, which lends a degree of anatomical specificity to the altered predictive processing resulting from OFC lesion. Overall, the altered magnitudes and time courses of MMN/P3a responses after lesions to the OFC indicate that the neural correlates of detection of auditory regularity violation is impacted at two hierarchical levels of rule abstraction. HighlightsO_LIOrbitofrontal lesions reduce auditory MMN to unpredicted tones at the local level (between tones within sequences) of the rule hierarchy in the Local-Global paradigm. C_LIO_LIOrbitofrontal lesions also impact combined local and global (between sequences) level auditory deviance response, as manifested by diminished and delayed MMN and delayed P3a. C_LI

neuroscience↗

bioRxiv2022

Asymmetric coding of reward prediction errors in human insula and dorsomedial prefrontal cortex

The signed value and unsigned salience of reward prediction errors (RPEs) are critical to understanding reinforcement learning (RL) and cognitive control. Dorsomedial prefrontal cortex (dMPFC) and insula (INS) are key regions for integrating reward and surprise information, but conflicting evidence for both signed and unsigned activity has led to competing proposals for the nature of RPE representations in these brain areas. Recently, the distributional RL theory (dRL) has been used to explain RPE coding diversity in the rodent midbrain by proposing that dopaminergic neurons have differential sensitivity to positive and negative RPEs. Here, we use intracranially recorded high frequency activity (HFA) to show that this asymmetric scaling strategy captures RPE coding diversity in human dMPFC and INS. We found neural populations responding to valence-specific positive and negative RPEs, as well as unsigned RPE salience, which are spatially interleaved within each region. Furthermore, directional connectivity estimates suggest a leading role of INS in communicating positive and unsigned RPEs to dMPFC. These findings support asymmetric scaling across distinct but intermingled neural populations as a core principle in RPE coding, expand the scope of dRL, and reconcile longstanding theoretical debates on the role of dMPFC and INS in RL and cognitive control.

neuroscience↗

bioRxiv2022

Subspace partitioning in human prefrontal cortex resolves cognitive interference

Human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task-features to guide subsequent behavior. The mechanisms by which the brain simultaneously encodes multiple task-relevant variables while minimizing interference from task-irrelevant features remain unknown. Leveraging intracranial recordings from the human PFC, we first demonstrate that competition between co-existing representations of past and present task variables incurs a behavioral switch cost. Our results reveal that this interference between past and present states in the PFC is resolved through coding partitioning into distinct low-dimensional neural states; thereby strongly attenuating behavioral switch costs. In sum, these findings uncover a fundamental coding mechanism that constitutes a central building block of flexible cognitive control.

neuroscience↗

bioRxiv2022

Auditory prediction hierarchy in the human hippocampus and amygdala

Our brains can extract structure from the environment and form predictions given past sensory experience. Predictive circuits have been identified in wide-spread cortical regions. However, the contribution of subcortical areas, such as the hippocampus and amygdala in the formation of predictions remains under-explored. Here, we hypothesized that the hippocampus would be sensitive to predictability in sound sequences, while the amygdala would be sensitive to unexpected violations of auditory rules. We presented epileptic patients undergoing presurgical monitoring with standard and deviant sounds, in a predictable or unpredictable context. Onsets of auditory responses and unpredictable deviance effects were detected at earlier latencies in the temporal cortex compared to the amygdala and hippocampus. Deviance effects in 1-20 Hz local field potentials were detected in the lateral temporal cortex, irrespective of predictability. The amygdala showed stronger deviance responses in the unpredictable context. Additionally, low frequency deviance responses in the hippocampus (1-8 Hz) were observed in the predictable but not in the unpredictable context. Our results reveal a distributed cortical-subcortical network underlying the generation of auditory predictions, comprising temporal cortex and the hippocampus and amygdala, and suggest that the neural basis of sensory predictions and prediction error signals needs to be extended to subcortical regions.

neuroscience↗

bioRxiv2022

Periodic neglect after frontoparietal lesions provides causal evidence for rhythmic attention sampling

Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time even in states of presumed sustained attention. Recent evidence suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results uncovered that frontoparietal lesions introduce periodic neglect, i.e., temporally-specific behavioral deficits that were aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with healthy controls during optimal phases but attenuated during the less excitable sub-cycles. Theta-dependent sampling (3 - 8 Hz) was causally dependent on prefrontal cortex, while alpha-band sampling (8 - 14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high amplitude, low frequency brain activity is not epiphenomenal, but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.

neuroscience↗

bioRxiv2022

Decision and response monitoring during working memory are sequentially represented in the human insula

Emerging research supports a role of the insula in human cognition. Here, we used intracranial EEG to investigate the spatiotemporal dynamics in the insula during a verbal working memory (vWM) task. We found robust effects for theta, beta, and high frequency activity (HFA) during probe presentation requiring a decision. Theta and beta band activity showed differential involvement across left and right insulae while sequential HFA modulations were observed along the anteroposterior axis. HFA in anterior insula tracked decision making and subsequent HFA was observed in posterior insula after the behavioral response. Our results provide electrophysiological evidence of engagement of different insula subregions in both decision-making and response monitoring during vWM and expand our knowledge of the role of the insula in complex human behavior.

neuroscience↗

bioRxiv2022

Personalized transcranial alternating current stimulation improves sleep quality: Initial Findings

Insufficient sleep is a major health issue. Inadequate sleep is associated with an array of poor health outcomes, including cardiovascular disease, diabetes, obesity, certain forms of cancer, Alzheimers disease, depression, anxiety, and suicidality. Given concerns with typical sedative hypnotic drugs for treating sleep difficulties, there is a compelling need for added alternative interventions. Here, we report results of a non-invasive electrical brain stimulation approach to optimizing sleep involving transcranial alternating current stimulation (tACS). A total of 25 participants (mean age: 46.3, S.D. {+/-}12.4, 15 females) were recruited for a null-stimulation controlled (Control condition), within subjects, randomized crossed design, that included two variants of an active condition involving 15 minutes pre-sleep tACS stimulation. To evaluate the impact on sleep quality, the two active tACS stimulation conditions were designed to modulate sleep-dependent neural activity in the theta/alpha frequency bands, with both stimulation types applied to all subjects in separate sessions. The first tACS condition used a fixed stimulation pattern across all participants, a pattern composed of stimulation at 5Hz and 10Hz. The second tACS condition used a personalized stimulation approach with the stimulation frequencies determined by each individuals peak EEG frequencies in the 4-6Hz and 9-11Hz bands. Personalized tACS stimulation increased sleep quantity (duration) by 22 minutes compared to a Control condition (p=.04), and 19 minutes compared to Fixed tACS stimulation (p=.03). Fixed stimulation did not significantly increase sleep duration compared to Control (mean: 3 minutes; p=0.75). For sleep onset, the Personalized tACS stimulation resulted in reducing the onset by 28% compared to the Fixed tACS stimulation (6 minutes faster, p=.02). For a Poor Sleep sub-group (n=13) categorized with Clinical Insomnia and with a high insomnia severity, Personalized tACS stimulation improved sleep duration by 33 minutes compared to Fixed stimulation (p=0.02), and 30 minutes compared to Control condition (p<0.1). Together, these results suggest that Personalized stimulation improves sleep quantity and time taken to fall asleep relative to Control and Fixed stimulation providing motivation for larger-scale trials for Personalized tACS as a sleep therapeutic, including for those with insomnia.

neuroscience↗

bioRxiv2022

Multi-areal neural dynamics encode human decision making

Value-based decision-making involves multiple cortical and subcortical brain areas, but the distributed nature of neurophysiological activity underlying economic choices in the human brain remains largely unexplored. Here, we use intracranial recordings from neurosurgical patients to show that risky choices are reflected in high frequency activity distributed across multiple prefrontal and subcortical brain regions, whereas reward-related computations are less widely represented and more modular. State space modeling reveals sub-second neural dynamics underlying choices during deliberation and allows high-accuracy trial-by-trial decoding of subjects choices robustly across patients despite differences in anatomical coverage. These results shed light into the neural basis of choice across brain areas and open the door to new intracranial approaches for brain state decoding.

neuroscience↗

bioRxiv2022

Representation of sustained visual experience by time-invariant distributed neural patterns

Instances of sustained stationary sensory input are ubiquitous. However, previous work focused almost exclusively on the transient onset responses. This presents a critical challenge for neural theories of consciousness, which should account for the full temporal extent of experience. Here we use intracranial recordings from human patients viewing diverse images in multiple durations. In sensory regions, we reveal that despite dramatic changes in activation magnitude, the distributed representation of categories and exemplars remains sustained and stable. In contrast, in frontoparietal regions we find transient content representation at stimulus onset. Our results highlight the connection between the anatomical and temporal correlates of experience. To the extent perception is sustained, it may rely on sensory representations, and to the extent it is discrete, centered on perceptual updating, it may rely on frontoparietal representations.

neuroscience↗

bioRxiv2022

To share or not to share? iEEG evidence for state-dependent inequity encoding in the human OFC

Social decision-making requires the integration of reward valuation and social cognition systems, both dependent on the orbitofrontal cortex (OFC). How these two OFC functions interact is largely unknown. We recorded intracranial activity from the OFC of ten patients making choices in the context of different types of inequity (disadvantageous vs. advantageous). We found that high-frequency activity (70-150 HZ) encoded the amount of self-reward, consistent with previous reports. We also observed novel evidence for encoding in human OFC of the social counterparts reward as well as the type of inequity being experienced. Additionally, we find social context modulates reward encoding: depending on inequity type, reward encoding was switched on and off rapidly within electrodes, across trials. These results provide direct evidence for explicit encoding of self- and other- rewards in the human OFC, and for rapid and reversible changes in encoding schemes driven by socially relevant contexts.

neuroscience↗