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Barnett, W. H.

Publications and source records attributed to Barnett, W. H..

4 recordsLinked to original sources

A piece-wise linear recurrent neural network identifies generalizable dynamics from neural activity during decision-making in rodents

Alterations in impulsivity characterize several neuropsychiatric disorders, however the neural processes that underlie an impulsive choice have not been identified. A recent body of literature suggests that there may be generalizable aspects of neural representations across animals. Whether this is also true for dynamic rather than just static (like geometrical) properties of neural representations, and specifically in the context of impulsive behaviors, is less clear. Therefore, the goal of this study is to characterize generalizable features of latent dynamics that disambiguate an impulsive from non-impulsive choice across many different data sets and animals. A deep learning-based latent factor model was constructed from neural recordings that were acquired in rat anterior cingulate cortex while performing a delay discounting task, which is commonly used to assess impulsivity. Prior work shows this brain region is critical for the performance of this task. We leveraged piecewise linear recurrent neural networks (PLRNNs) to perform a nonlinear latent factor analysis across animals and experimental sessions. Our PLRNN explained a substantially larger percent of variance in fewer dimensions than linear approaches. We cross-validated performance of the model on test data and following the disruption of recurrent connectivity or auto-regressive latent dynamics. These tests confirmed that our fitting procedure consistently embedded generalizable neuronal dynamics within the PLRNN. Further, we found that the latent dynamics exhibited strong rotational features and progressed faster for impulsive choices. In summary, our model captures properties of the latent dynamics that are consistent across multiple data sets and disambiguate impulsive choices.

neuroscience↗

Striatal compartments participate in multi-modal and concurrent reward-based learning

Cortical and basal ganglia circuits play a crucial role in the formation of goal-directed and habitual behaviors. In this study, we investigate the cortico-striatal circuitry involved in learning and the role of this circuitry in the emergence of inflexible behaviors such as those observed in addiction. Specifically, we develop a computational model of cortico-striatal interactions that performs concurrent goal-directed and habit learning. The model accomplishes this by distinguishing learning processes in the dorsomedial striatum (DMS) that rely on reward prediction error signals as distinct from the dorsolateral striatum (DLS) where learning is supported by salience signals. These striatal subregions each operate on unique cortical input: the DMS receives input from the prefrontal cortex (PFC) which represents outcomes, and the DLS receives input from the premotor cortex which determines action selection. Following an initial learning of a two-alternative forced choice task, we subjected the model to reversal learning, reward devaluation, and learning a punished outcome. Behavior driven by stimulus-response associations in the DLS resisted goal-directed learning of new reward feedback rules despite devaluation or punishment, indicating the expression of habit. We repeated these simulations after the impairment of executive control, which was implemented as poor outcome representation in the PFC. The degraded executive control reduced the efficacy of goal-directed learning, and stimulus-response associations in the DLS were even more resistant to the learning of new reward feedback rules. In summary, this model describes how circuits of the dorsal striatum are dynamically engaged to control behavior and how the impairment of executive control by the PFC enhances inflexible behavior. Author SummarySubstance abuse changes an animals brain so that it is not able to appropriately respond to new environmental cues such as negative consequences for drug use. It is thought that the transition from adaptive to inflexible responding involves the inappropriate engagement of neural circuitry responsible for habit. In this study, we model neural circuitry that is critical for adaptive responding to changes in reward feedback to animal behavior. We extended previous computational models of the basal ganglia to incorporate detailed biophysical representations of the dorsomedial striatum, which is critical for goal-directed behavior, and the dorsolateral striatum, which is critical for habitual behavior. The model exhibited learning in simulations of reward reversal, devaluation, and punished outcome tasks. Recent work from our group has quantified the impairment of executive control in cortical activity of compulsively drinking rats. Here, we challenged the model in additional simulations by implementing the impairment of executive control as a reduction in the fidelity of prefrontal cortical outcome representations. Our results illustrate how impaired executive control reduces the performance of goal-directed learning and, hence, reduces the models ability to overcome an established habitual response.

neuroscience↗

Heartbeats entrain breathing via baroreceptor-mediated modulation of expiratory activity

Cardio-ventilatory coupling refers to a heartbeat (HB) occurring at a preferred latency before the onset of the next breath. We hypothesized that the pressure pulse generated by a HB activates baroreceptors that modulates brainstem expiratory neuronal activity and delays the initiation of inspiration. In supine male subjects, we recorded ventilation, electrocardiogram, and blood pressure during 20-min epochs of baseline, slow-deep breathing, and recovery. In in situ rodent preparations, we recorded brainstem activity in response to pulses of perfusion pressure. We applied a well-established respiratory network model to interpret these data. In humans, the latency between HBs and onset of inspiration was consistent across different breathing patterns. In in situ preparations, a transient pressure pulse during expiration activated a subpopulation of expiratory neurons normally active during post-inspiration; thus, delaying the next inspiration. In the model, baroreceptor input to post-inspiratory neurons accounted for the effect. These studies are consistent with baroreflex activation modulating respiration through a pauci-synaptic circuit from baroreceptors to onset of inspiration.

neuroscience↗

Inhibitory control of active expiration by the Botzinger complex in rats

The expiratory neurons of the Botzinger complex (BotC) provide inhibitory inputs to the respiratory network, which, during eupnea, are critically important for respiratory phase transition and duration control. Herein, we investigated how the BotC neurons interact with the expiratory oscillator located in the parafacial respiratory group (pFRG) and control the abdominal activity during active expiration. Using the decerebrated, arterially perfused in situ rat preparations, we recorded the neuronal activity and performed pharmacological manipulations of the BotC and pFRG during hypercapnia or after the exposure to short-term sustained hypoxia - conditions that generate active expiration. The experimental data were integrated in a mathematical model to gain new insights in the inhibitory connectome within the respiratory central pattern generator. Our results reveal a complex inhibitory circuitry within the BotC that provides inhibitory inputs to the pFRG thus restraining abdominal activity under resting conditions and contributing to abdominal expiratory pattern formation during active expiration.

physiology↗