Biology subjects

Berke, J.

Publications and source records attributed to Berke, J..

9 recordsLinked to original sources

bioRxiv2026

Divergent Dopamine Dynamics within the Accumbens Core

Dopamine in the nucleus accumbens Core powerfully influences motivation and learning, yet the information encoded by Core dopamine remains unresolved. Competing theories typically assume a spatially uniform signal, and standard recording methods average dopamine over substantial tissue volumes. Using two-photon imaging through microprisms in behaving mice, we reveal a pronounced spatial organization of Core dopamine dynamics. Posterior Core showed phasic dopamine increases to both rewards and aversive stimuli, with transfer to a predictive cue after learning. Anterior Core showed phasic decreases to aversive stimuli, weaker increases to reward, and higher tonic dopamine that was further amplified by cocaine. Rather than uniform or highly fragmented signals, the Core contains a smoothly graded mixture between two distinct sets of dopamine dynamics, neither matching canonical reward prediction errors.

neuroscience↗

bioRxiv2025

Need-selective gating of dopamine neuron cue responses by real and virtual hunger

The midbrain dopamine system is important for linking reward-predictive cues to learning and 20 motivation. Here we investigated how dopamine neuron responses to food and water cues are modulated by changes in internal state. We developed a flexible cued-approach task that allowed us to examine behavioral and neural responses to both food- and water-predictive cues within the same recording session. We found that overlapping subsets of dopamine neurons respond to food and water cues, but that the magnitude of these responses is gated in a need-25 specific way. Stimulation of hunger-promoting AgRP neurons amplified dopamine neuronresponses to food cues, but not water cues, and the magnitude of these responses exceeded those observed in natural hunger. These findings indicate that changes in internal state modulate, in a need-appropriate way, the responses of a common set of dopamine neurons to environmental signals of food and water availability.

neuroscience↗

bioRxiv2021

Striatal dopamine pulses follow a temporal discounting spectrum

Dopamine input to striatum can encode reward prediction error, a critical signal for updating predictions of future rewards. However, it is unclear how this mechanism handles the need to make predictions, and provide feedback, over multiple time horizons: from seconds or less (if singing a song) to potentially hours or more (if hunting for food). Here we report that dopamine pulses in distinct striatal subregions convey reward prediction errors over distinct temporal scales. Dopamine dynamics systematically accelerated from ventral to dorsal-medial to dorsal-lateral striatum, in the tempo of their spontaneous fluctuations, their integration of prior rewards, and their discounting of future rewards. This spectrum of time scales for value computations can help achieve efficient learning and adaptive motivation for a wide range of behaviors.

neuroscience↗

bioRxiv2020

Sleep spindles coordinate corticostriatal reactivations during the emergence of automaticity

Plasticity within the corticostriatal network is known to regulate the balance between behavioral flexibility and automaticity. Repeated training of an action has been shown to bias behavior towards automaticity, suggesting that training may trigger activity-dependent corticostriatal plasticity. However, surprisingly little is known about the natural activity patterns that may drive plasticity or when they occur during long-term training. Here we chronically monitored neural activity from primary motor cortex (M1) and the dorsolateral striatum (DLS) during both training and offline periods, i.e., time away from training including sleep, throughout the development of an automatic reaching action. We first show that blocking striatal NMDA receptors during offline periods prevents the emergence of behavioral consistency, a hallmark of automaticity. We then show that, throughout the development of an automatic reaching action, corticostriatal functional connectivity increases during offline periods. Such increases track the emergence of consistent behavior and predictable cross-area neural dynamics. We then identify sleep spindles during non-REM sleep (NREM) as uniquely poised to mediate corticostriatal plasticity during offline periods. We show that sleep spindles are periods of maximal corticostriatal transmission within offline periods, that sleep spindles in post-training NREM reactivate neurons across areas, and that sleep-spindle modulation in post-training NREM is linked to observable changes in spiking relationships between individual pairs of M1 and DLS neurons. Our results indicate that offline periods, in general, and sleep spindles, specifically, play an important role in regulating behavioral flexibility through corticostriatal network plasticity.

neuroscience↗

bioRxiv2020

Cellular-scale silicon probes for high-density, precisely-localized neurophysiology

Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared to the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at cellular-scale (5x10{micro}m cross-section), with ultra-high-density packing (as little as 66{micro}m between shanks) and 64 or 256 closely-spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and maintain high-quality spike recordings in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal {micro}-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits, and potentially for human brain-machine interfaces.

bioengineering↗

bioRxiv2020

Globus pallidus dynamics reveal covert strategies for behavioral inhibition.

Flexible behavior requires restraint or cancellation of actions that are no longer appropriate. This behavioral inhibition critically relies on frontal cortex - basal ganglia circuits. A central node within the basal ganglia, the globus pallidus pars externa (GPe), has been hypothesized to mediate "proactive" inhibition: being prepared to stop an action if needed. Here we investigate the population dynamics of rat GPe neurons during preparation-to-stop, stopping, and going. Rats could selectively engage proactive inhibition towards one specific action, as shown by slowed reaction times (RTs) for that action. While proactive inhibition was engaged, GPe population activity occupied state-space locations farther from the trajectory followed during normal movement initiation. Furthermore, the specific state-space location was predictive of distinct types of errors: failures to stop, failures to go, and incorrect choices. The slowed RTs on correct proactive trials reflected a starting bias towards the alternative action, which was overcome before making progress towards action initiation. Our results demonstrate that rats can exert cognitive control via strategic positioning of their GPe network state.

neuroscience↗

bioRxiv2018

Knock-in rats expressing Cre and Flp recombinases at the Parvalbumin locus.

Rats have the ability to learn and perform sophisticated behavioral tasks, making them very useful for investigating neural circuit functions. In contrast to the extensive mouse genetic toolkit, the paucity of recombinase-expressing rat models has limited the ability to monitor and manipulate molecularly-defined neural populations in this species. Here we report the generation and validation of two knock-in rat strains expressing either Cre or Flp recombinase under the control of Parvalbumin (Pvalb), a gene expressed in the critical \"fast-spiking\" subset of inhibitory interneurons (FSIs). These strains were generated with CRISPR-Cas9 gene editing and show highly specific and penetrant labeling of Pvalb-expressing neurons, as demonstrated by in situ hybridization and immunohistochemistry. We validated these models in both prefrontal cortex and striatum using both ex vivo and in vivo approaches, including whole-cell recording, optogenetics, extracellular physiology and photometry. Our results demonstrate the utility of these new transgenic models for a wide range of neuroscience experiments.

neuroscience↗

bioRxiv2018

Forebrain dopamine value signals arise independently from midbrain dopamine cell firing.

The mesolimbic dopamine projection from the ventral tegmental area (VTA) to nucleus accumbens (NAc) is a key pathway for reward-driven learning, and for the motivation to work for more rewards. VTA dopamine cell firing can encode reward prediction errors (RPEs1,2), vital learning signals in computational theories of adaptive behavior. However, NAc dopamine release more closely resembles reward expectation (value), a motivational signal that invigorates approach behaviors3-7. This discrepancy might be due to distinct behavioral contexts: VTA dopamine cells have been recorded under head-fixed conditions, while NAc dopamine release has been measured in actively-moving subjects. Alternatively the mismatch may reflect changes in the tonic firing of dopamine cells8, or a fundamental dissociation between firing and release. Here we directly compare dopamine cell firing and release in the same adaptive decision-making task. We show that dopamine release covaries with reward expectation in two specific forebrain hotspots, NAc core and ventral prelimbic cortex. Yet the firing rates of optogenetically-identified VTA dopamine cells did not correlate with reward expectation, but instead showed transient, error-like responses to unexpected cues. We conclude that critical motivation-related dopamine dynamics do not arise from VTA dopamine cell firing, and may instead reflect local influences over forebrain dopamine varicosities.

neuroscience↗

bioRxiv2017

Sensorimotor Processing In The Basal Ganglia Leads To Transient Beta Oscillations During Behavior

Brief epochs of beta oscillations have been implicated in sensorimotor control in the basal ganglia of task-performing healthy animals. However, which neural processes underlie their generation and how they are affected by sensorimotor processing remains unclear. To determine the mechanisms underlying transient beta oscillations in the local field potential (LFP), we combined computational modeling of the subthalamo-pallidal network for the generation of beta oscillations with realistic stimulation patterns derived from single unit data. The single unit data were recorded from different basal ganglia subregions in rats performing a cued choice task. In the recordings we found distinct firing patterns in the striatum, globus pallidus and subthalamic nucleus related to sensory and motor events during the behavioral task. Using these firing patterns to generate realistic inputs to our network model lead to transient beta oscillations with the same time course as the rat LFP data. In addition, our model can account for further non-intuitive aspects of beta modulation, including beta phase resets following sensory cues and correlations with reaction time. Overall, our model can explain how the combination of temporally regulated sensory responses of the subthalamic nucleus, ramping activity of the subthalamic nucleus, and movement-related activity of the globus pallidus, leads to transient beta oscillations during behavior.\n\nSignificance StatementTransient beta oscillations emerge in the normal functioning cortico-basal ganglia loop during behavior. In this work we employ a unique approach connecting a computational model closely with experimental data. In this way we achieve a simulation environment for our model that mimics natural input patterns in awake behaving animals. Using this approach we demonstrate that a computational model for beta oscillations in Parkinsons disease can also account for complex patterns of transient beta oscillations in healthy animals. Therefore, we propose that transient beta oscillations in healthy animals share the same mechanism with pathological beta oscillations in Parkinsons disease. This important result connects functional and pathological roles of beta oscillations in the basal ganglia.

neuroscience↗