Biology subjects

Hughes, N. C.

Publications and source records attributed to Hughes, N. C..

4 recordsLinked to original sources

bioRxiv2024

Mesolimbic local field potentials are modulated by motor control

Background and ObjectivesWhile historically cortico-basal ganglia-thalamocortical loops were believed to process limbic and sensorimotor data in parallel, there is now evidence to suggest that the two information streams can be processed in a single open loop. However, the limbic-motor interface remains insufficiently characterized. We sought to further investigate how extrastriatal regions may regulate motor output by examining electrophysiological activity in these areas during a response inhibition paradigm. MethodsWe recorded local field potentials (LFPs) from epilepsy patients implanted with intracranial depth electrodes for seizure localization purposes. Participants performed the stop-signal task, during which they made speeded choice reactions to "go" stimuli and occasionally inhibited their reactions in the incident of a "stop" signal. To compare power during movement and the absence of movement, we applied a Wilcoxon signed-rank test. Additionally, we performed a linear mixed-effects model to relate power in limbic regions to power in the motor cortex. Finally, we implemented exploratory analyses to identify power differences for correct go versus correct stop trials and for correct stop versus incorrect stop trials using cluster-based permutation testing. Results14 patients participated. A comparison between movement and baseline fixation revealed that motor response is associated with reduced beta (15-35 Hz) power in the amygdala, hippocampus, and motor cortex and reduced gamma (35-100 Hz) power in the amygdala and hippocampus. Moreover, average beta and gamma power in the amygdala and hippocampus during motor execution were positively associated with average beta and gamma power in the motor cortex. Additionally, we identified significant differences between correct go and stop trials in delta (1-4 Hz) power for all three regions and in theta (4-8 Hz) power for the amygdala and motor cortex. Likewise, we identified significant differences between correct and incorrect stop trials in delta power for the hippocampus and motor cortex, in theta power for the motor cortex, in alpha (8-15 Hz) and beta power for the amygdala and motor cortex, and in gamma power for all three areas. DiscussionThese correlations between neural oscillations in the hippocampus and amygdala and movement strengthen the notion of mesolimbic modulation of motor activity.

neuroscience↗

bioRxiv2024

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking. Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient. Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex (p=0.0022), high-gamma in the anterior cingulate (p=0.0004), and high-gamma in the insula (p=0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power (p=2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex (p=2.0E-4), broad frequencies in amygdala (p=2.0E-4), and theta to low-gamma in insula (p=4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal (p=0.0048) and with patient impulsivity (p=0.00478). Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.

neuroscience↗

bioRxiv2024

Depression Attenuates Caudate and Dorsolateral Prefrontal Cortex Alpha and Beta Power Response to Reward

Depression is a prevalent psychiatric condition and a common comorbidity across neurological disorders. Common symptoms include anhedonia, negative emotional biases, and cognitive dysfunction. Beta (15-30 Hz) neural oscillations have been shown to increase during reward-based learning within fronto-striatal reward networks. Corticostriatal beta oscillations have also been implicated in cognitive functions including working memory. However, the relationship between beta oscillations and depression remains unknown. Using intracranial recordings, we aimed to investigate how depression modulates the spectral power of neural oscillations in corticostriatal structures during reward feedback in a working memory task. Thirty movement disorder patients undergoing awake deep brain stimulation surgery with electrode trajectories traversing the caudate or dorsolateral prefrontal cortex (DLPFC) participated in this study. We recorded local field potential data intraoperatively as subjects completed a 2-back verbal working memory task where they identified whether a word matched the word presented two trials prior. Subjects received reward in the form of visual feedback for correct answers. Word stimuli had either a positive, negative, or neutral emotional valence. Subjects completed the Beck Depression Inventory-II preoperatively, and we used a cut-off score of 14 to identify patients with depression. We found that caudate and DLPFC power increased in the alpha (8-15 Hz) and beta range during reward feedback and that this increase was significantly greater for subjects without depression compared to depressed subjects. In non-depressed patients, positive feedback stimuli evoked significantly higher beta power in the caudate during reward compared to neutral and negative stimuli. In depressed patients, emotional valence did not affect reward-related caudate spectral power, while DLPFC alpha power was significantly higher following positive emotional stimuli in comparison to neutral but not negative stimuli. We additionally found that anti-depressant medications (ADMs) generally blunted alpha and beta reward signaling processes in the DLPFC. This blunting effect on reward-related alpha power in the DLPFC, however, was reversed in depressed patients, indicating that the effects of ADMs on reward signaling processes may depend on whether a patient is exhibiting depression symptoms. Our findings suggest that depression suppresses the alpha and beta power response to both reward and emotional stimuli during working memory, indicating power attenuation in these frequency bands may contribute to emotional and cognitive depression symptoms.

neuroscience↗

bioRxiv2019

A functional cortical network for sensorimotor sequence generation

The brain generates complex sequences of movements that can be flexibly reconfigured in real-time based on sensory feedback, but how this occurs is not fully understood. We developed a novel sequence licking task in which mice directed their tongue to a target that moved through a series of locations. Mice could rapidly reconfigure the sequence online based on tactile feedback. Closed-loop optogenetics and electrophysiology revealed that tongue/jaw regions of somatosensory (S1TJ) and motor (M1TJ) cortex encoded and controlled tongue kinematics at the level of individual licks. Tongue premotor (anterolateral motor, ALM) cortex encoded intended tongue angle in a smooth manner that spanned individual licks and even whole sequences, and progress toward the reward that marked successful sequence execution. ALM activity regulated sequence initiation, but multiple cortical areas collectively controlled termination of licking. Our results define a functional cortical network for hierarchical control of sensory- and reward-guided orofacial sequence generation.

neuroscience↗