Striatal
striatal
Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons
Join Us for the Memory Decoding Journal Club! A collaboration of the Carboncopies Foundation and BPF Aspirational Neuroscience. This time, we’re diving into a groundbreaking paper: "Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons
Neuromodulation of striatal D1 cells shapes BOLD fluctuations in anatomically connected thalamic and cortical regions
Understanding how macroscale brain dynamics are shaped by microscale mechanisms is crucial in neuroscience. We investigate this relationship in animal models by directly manipulating cellular properties and measuring whole-brain responses using resting-state fMRI. Specifically, we explore the impact of chemogenetically neuromodulating D1 medium spiny neurons in the dorsomedial caudate putamen (CPdm) on BOLD dynamics within a striato-thalamo-cortical circuit in mice. Our findings indicate that CPdm neuromodulation alters BOLD dynamics in thalamic subregions projecting to the dorsomedial striatum, influencing both local and inter-regional connectivity in cortical areas. This study contributes to understanding structure–function relationships in shaping inter-regional communication between subcortical and cortical levels.
Off-policy learning in the basal ganglia
I will discuss work with Jack Lindsey modeling reinforcement learning for action selection in the basal ganglia. I will argue that the presence of multiple brain regions, in addition to the basal ganglia, that contribute to motor control motivates the need for an off-policy basal ganglia learning algorithm. I will then describe a biological implementation of such an algorithm that predicts tuning of dopamine neurons to a quantity we call "action surprise," in addition to reward prediction error. In the same model, an implementation of learning from a motor efference copy also predicts a novel solution to the problem of multiplexing feedforward and efference-related striatal activity. The solution exploits the difference between D1 and D2-expressing medium spiny neurons and leads to predictions about striatal dynamics.
Hallucinating mice, dopamine and immunity; towards mechanistic treatment targets for psychosis
Hallucinations are a core symptom of psychotic disorders and have traditionally been difficult to study biologically. We developed a new behavioral computational approach to measure hallucinations-like perception in humans and mice alike. Using targeted neural circuit manipulations, we identified a causal role for striatal dopamine in mediating hallucination-like perception. Building on this, we currently investigate the neural and immunological upstream regulators of these dopaminergic circuits with the goal to identify new biological treatment targets for psychosis
Integration of 3D human stem cell models derived from post-mortem tissue and statistical genomics to guide schizophrenia therapeutic development
Schizophrenia is a neuropsychiatric disorder characterized by positive symptoms (such as hallucinations and delusions), negative symptoms (such as avolition and withdrawal) and cognitive dysfunction1. Schizophrenia is highly heritable, and genetic studies are playing a pivotal role in identifying potential biomarkers and causal disease mechanisms with the hope of informing new treatments. Genome-wide association studies (GWAS) identified nearly 270 loci with a high statistical association with schizophrenia risk; however each locus confers only a small increase in risk therefore it is difficult to translate these findings into understanding disease biology that can lead to treatments. Induced pluripotent stem cell (iPSC) models are a tractable system to translate genetic findings and interrogate mechanisms of pathogenesis. Mounting research with patient-derived iPSCs has proposed several neurodevelopmental pathways altered in SCZ, such as neural progenitor cell (NPC) proliferation, imbalanced differentiation of excitatory and inhibitory cortical neurons. However, it is unclear what exactly these iPS models recapitulate, how potential perturbations of early brain development translates into illness in adults and how iPS models that represent fetal stages can be utilized to further drug development efforts to treat adult illness. I will present the largest transcriptome analysis of post-mortem caudate nucleus in schizophrenia where we discovered that decreased presynaptic DRD2 autoregulation is the causal dopamine risk factor for schizophrenia (Benjamin et al, Nature Neuroscience 2022 https://doi.org/10.1038/s41593-022-01182-7). We developed stem cell models from a subset of the postmortem cohort to better understand the molecular underpinnings of human psychiatric disorders (Sawada et al, Stem Cell Research 2020). We established a method for the differentiation of iPS cells into ventral forebrain organoids and performed single cell RNAseq and cellular phenotyping. To our knowledge, this is the first study to evaluate iPSC models of SZ from the same individuals with postmortem tissue. Our study establishes that striatal neurons in the patients with SCZ carry abnormalities that originated during early brain development. Differentiation of inhibitory neurons is accelerated whereas excitatory neuronal development is delayed, implicating an excitation and inhibition (E-I) imbalance during early brain development in SCZ. We found a significant overlap of genes upregulated in the inhibitory neurons in SCZ organoids with upregulated genes in postmortem caudate tissues from patients with SCZ compared with control individuals, including the donors of our iPS cell cohort. Altogether, we demonstrate that ventral forebrain organoids derived from postmortem tissue of individuals with schizophrenia recapitulate perturbed striatal gene expression dynamics of the donors’ brains (Sawada et al, biorxiv 2022 https://doi.org/10.1101/2022.05.26.493589).
Chemistry of the adaptive mind: lessons from dopamine
The human brain faces a variety of computational dilemmas, including the flexibility/stability, the speed/accuracy and the labor/leisure tradeoff. I will argue that striatal dopamine is particularly well suited to dynamically regulate these computational tradeoffs depending on constantly changing task demands. This working hypothesis is grounded in evidence from recent studies on learning, motivation and cognitive control in human volunteers, using chemical PET, psychopharmacology, and/or fMRI. These studies also begin to elucidate the mechanisms underlying the huge variability in catecholaminergic drug effects across different individuals and across different task contexts. For example, I will demonstrate how effects of the most commonly used psychostimulant methylphenidate on learning, Pavlovian and effortful instrumental control depend on fluctuations in current environmental volatility, on individual differences in working memory capacity and on opportunity cost respectively.
Dyskinesia: the failure of dopamine-dependent motor control
Mechanisms and Roles of Fast Dopamine Signaling
Dopamine is a neuromodulator that codes information on various time scales. I will discuss recent progress on the identification of fast release mechanisms for dopamine in the mouse striatum. I will present data on triggering mechanisms of dopamine release and evaluate its roles in striatal regulation. In the long-term, our work will allow for a better understanding of the mechanisms and time scales of dopamine coding in health and disease.
Dynamic dopaminergic signaling probabilistically controls the timing of self-timed movements
Human movement disorders and pharmacological studies have long suggested molecular dopamine modulates the pace of the internal clock. But how does the endogenous dopaminergic system influence the timing of our movements? We examined the relationship between dopaminergic signaling and the timing of reward-related, self-timed movements in mice. Animals were trained to initiate licking after a self-timed interval following a start cue; reward was delivered if the animal’s first lick fell within a rewarded window (3.3-7 s). The first-lick timing distributions exhibited the scalar property, and we leveraged the considerable variability in these distributions to determine how the activity of the dopaminergic system related to the animals’ timing. Surprisingly, dopaminergic signals ramped-up over seconds between the start-timing cue and the self-timed movement, with variable dynamics that predicted the movement/reward time, even on single trials. Steeply rising signals preceded early initiation, whereas slowly rising signals preceded later initiation. Higher baseline signals also predicted earlier self-timed movement. Optogenetic activation of dopamine neurons during self-timing did not trigger immediate movements, but rather caused systematic early-shifting of the timing distribution, whereas inhibition caused late-shifting, as if dopaminergic manipulation modulated the moment-to-moment probability of unleashing the planned movement. Consistent with this view, the dynamics of the endogenous dopaminergic signals quantitatively predicted the moment-by-moment probability of movement initiation. We conclude that ramping dopaminergic signals, potentially encoding dynamic reward expectation, probabilistically modulate the moment-by-moment decision of when to move. (Based on work from Hamilos et al., eLife, 2021).
Neurocognitive mechanisms of proactive temporal attention: challenging oscillatory and cortico-centered models
To survive in a rapidly dynamic world, the brain predicts the future state of the world and proactively adjusts perception, attention and action. A key to efficient interaction is to predict and prepare to not only “where” and “what” things will happen, but also to “when”. I will present studies in healthy and neurological populations that investigated the cognitive architecture and neural basis of temporal anticipation. First, influential ‘entrainment’ models suggest that anticipation in rhythmic contexts, e.g. music or biological motion, uniquely relies on alignment of attentional oscillations to external rhythms. Using computational modeling and EEG, I will show that cortical neural patterns previously associated with entrainment in fact overlap with interval timing mechanisms that are used in aperiodic contexts. Second, temporal prediction and attention have commonly been associated with cortical circuits. Studying neurological populations with subcortical degeneration, I will present data that point to a double dissociation between rhythm- and interval-based prediction in the cerebellum and basal ganglia, respectively, and will demonstrate a role for the cerebellum in attentional control of perceptual sensitivity in time. Finally, using EEG in neurodegenerative patients, I will demonstrate that the cerebellum controls temporal adjustment of cortico-striatal neural dynamics, and use computational modeling to identify cerebellar-controlled neural parameters. Altogether, these findings reveal functionally and neural context-specificity and subcortical contributions to temporal anticipation, revising our understanding of dynamic cognition.
Striatal circuitry for reward learning and decision-making
Striatal circuits underlying sensorimotor functions
Striatal Circuitry
Hallucinating mice and dopamine – towards mechanistic treatment targets for psychosis
Psychotic disorders are devastating conditions without any mechanistic treatment available. One major hurdle in the biological study of psychosis is the challenge of rigorously probing this condition in pre-clinical animal models. The goal of our research is to develop and exploit innovative frameworks for the study of psychosis in mice. In our present work, where we developed a cross-species computational psychiatry approach to probe hallucination-like perception. This enabled us to directly relate human and mouse behavior, and to demonstrate and dissect the causal role of striatal dopamine in hallucination-like perception. Our results suggest a neural circuit mechanism for the long-standing dopamine hypothesis of psychosis, and provide a new translational framework for the biological study of psychosis. This opens up exciting possibilities for advancing the biological understanding of psychosis and to identify mechanistic treatment targets.
Striatal mechanisms underlying vulnerability for punishment-resistant alcohol drinking
The Corticostriatal Pathway
Experience-dependent remapping of temporal encoding by striatal ensembles
Medium-spiny neurons (MSNs) in the striatum are required for interval timing, or the estimation of the time over several seconds via a motor response. We and others have shown that striatal MSNs can encode the duration of temporal intervals via time-dependent ramping activity, progressive monotonic changes in firing rate preceding behaviorally salient points in time. Here, we investigated how timing-related activity within striatal ensembles changes with experience. We leveraged a rodent-optimized interval timing task in which mice ‘switch’ response ports after an amount of time has passed without reward. We report three main results. First, we found that the proportion of MSNs exhibiting time-dependent modulations of firing rate increased after 10 days of task overtraining. Second, temporal decoding by MSN ensembles increased with experience and was largely driven by time-related ramping activity. Finally, we found that time-related ramping activity generalized across both correct and error trials. These results enhance our understanding of striatal temporal processing by demonstrating that time-dependent activity within MSN ensembles evolves with experience and is dissociable from motor- and reward-related processes.
Pulvinar and striatal circuits for auditory processing and behaviors
Effects of stress and local striatal circuitry on motivated behaviors
The role of spatiotemporal waves in coordinating regional dopamine decision signals
The neurotransmitter dopamine is essential for normal reward learning and motivational arousal processes. Indeed these core functions are implicated in the major neurological and psychiatric dopamine disorders such as schizophrenia, substance abuse disorders/addiction and Parkinson's disease. Over the years, we have made significant strides in understanding the dopamine system across multiple levels of description, and I will focus on our recent advances in the computational description, and brain circuit mechanisms that facilitate the dual role of dopamine in learning and performance. I will specifically describe our recent work with imaging the activity of dopamine axons and measurements of dopamine release in mice performing various behavioural tasks. We discovered wave-like spatiotemporal activity of dopamine in the striatal region, and I will argue that this pattern of activation supports a critical computational operation; spatiotemporal credit assignment to regional striatal subexperts. Our findings provide a mechanistic description for vectorizing reward prediction error signals relayed by dopamine.
Male songbirds turn off their self-evaluation systems when they sing to females
Attending to mistakes while practicing alone provides opportunities for learning but self-evaluation during audience-directed performance could distract from ongoing execution. It remains unknown how animals switch between practice and performance modes, and how evaluation systems process errors across distinct performance contexts. We recorded from striatal-projecting dopamine (DA) neurons as male songbirds transitioned from singing alone to singing female-directed courtship song. In the presence of the female, singing-related performance error signals were reduced or gated off and DA neurons were instead phasically activated by female vocalizations. Mesostriatal DA neurons can thus dynamically change their tuning with changes in social context.
Delineating Reward/Avoidance Decision Process in the Impulsive-compulsive Spectrum Disorders through a Probabilistic Reversal Learning Task
Impulsivity and compulsivity are behavioural traits that underlie many aspects of decision-making and form the characteristic symptoms of Obsessive Compulsive Disorder (OCD) and Gambling Disorder (GD). The neural underpinnings of aspects of reward and avoidance learning under the expression of these traits and symptoms are only partially understood. " "The present study combined behavioural modelling and neuroimaging technique to examine brain activity associated with critical phases of reward and loss processing in OCD and GD. " "Forty-two healthy controls (HC), forty OCD and twenty-three GD participants were recruited in our study to complete a two-session reinforcement learning (RL) task featuring a “probability switch (PS)” with imaging scanning. Finally, 39 HC (20F/19M, 34 yrs +/- 9.47), 28 OCD (14F/14M, 32.11 yrs ±9.53) and 16 GD (4F/12M, 35.53yrs ± 12.20) were included with both behavioural and imaging data available. The functional imaging was conducted by using 3.0-T SIEMENS MAGNETOM Skyra syngo MR D13C at Monash Biomedical Imaging. Each volume compromised 34 coronal slices of 3 mm thickness with 2000 ms TR and 30 ms TE. A total of 479 volumes were acquired for each participant in each session in an interleaved-ascending manner. " " The standard Q-learning model was fitted to the observed behavioural data and the Bayesian model was used for the parameter estimation. Imaging analysis was conducted using SPM12 (Welcome Department of Imaging Neuroscience, London, United Kingdom) in the Matlab (R2015b) environment. The pre-processing commenced with the slice timing, realignment, normalization to MNI space according to T1-weighted image and smoothing with a 8 mm Gaussian kernel. " " The frontostriatal brain circuit including the putamen and medial orbitofrontal (mOFC) were significantly more active in response to receiving reward and avoiding punishment compared to receiving an aversive outcome and missing reward at 0.001 with FWE correction at cluster level; While the right insula showed greater activation in response to missing rewards and receiving punishment. Compared to healthy participants, GD patients showed significantly lower activation in the left superior frontal and posterior cingulum at 0.001 for the gain omission. " " The reward prediction error (PE) signal was found positively correlated with the activation at several clusters expanding across cortical and subcortical region including the striatum, cingulate, bilateral insula, thalamus and superior frontal at 0.001 with FWE correction at cluster level. The GD patients showed a trend of decreased reward PE response in the right precentral extending to left posterior cingulate compared to controls at 0.05 with FWE correction. " " The aversive PE signal was negatively correlated with brain activity in regions including bilateral thalamus, hippocampus, insula and striatum at 0.001 with FWE correction. Compared with the control group, GD group showed an increased aversive PE activation in the cluster encompassing right thalamus and right hippocampus, and also the right middle frontal extending to the right anterior cingulum at 0.005 with FWE correction. " " Through the reversal learning task, the study provided a further support of the dissociable brain circuits for distinct phases of reward and avoidance learning. Also, the OCD and GD is characterised by aberrant patterns of reward and avoidance processing.
Striatal circuits for reward learning and decision-making
How are actions linked with subsequent outcomes to guide choices? The nucleus accumbens (NAc), which is implicated in this process, receives glutamatergic inputs from the prelimbic cortex (PL) and midline regions of the thalamus (mTH). However, little is known about what is represented in PL or mTH neurons that project to NAc (PL-NAc and mTH-NAc). By comparing these inputs during a reinforcement learning task in mice, we discovered that i) PL-NAc preferentially represents actions and choices, ii) mTH-NAc preferentially represents cues, iii) choice-selective activity in PL-NAc is organized in sequences that persist beyond the outcome. Through computational modelling, we demonstrate that these sequences can support the neural implementation of temporal difference learning, a powerful algorithm to connect actions and outcomes across time. Finally, we test and confirm predictions of our circuit model by direct manipulation of PL-NAc neurons. Thus, we integrate experiment and modelling to suggest a neural solution for credit assignment.
Improved striatal learning with vector-valued errors mediated by diffusely transmitted dopamine
COSYNE 2022
Improved striatal learning with vector-valued errors mediated by diffusely transmitted dopamine
COSYNE 2022
Indirect-projecting striatal neurons constrain timed action via ‘ramping’ activity.
COSYNE 2022
Indirect-projecting striatal neurons constrain timed action via ‘ramping’ activity.
COSYNE 2022
Regionally distinct striatal circuits support broadly opponent aspects of action suppression and production
COSYNE 2022
Regionally distinct striatal circuits support broadly opponent aspects of action suppression and production
COSYNE 2022
A striatal probabilistic population code for reward underlies distributional reinforcement learning
COSYNE 2022
A striatal probabilistic population code for reward underlies distributional reinforcement learning
COSYNE 2022
Controlling human cortical and striatal reinforcement learning with meta prediction error
COSYNE 2023
Striatal dopamine encodes movement and value at distinct time points
COSYNE 2023
Striatal pathways oppositely shift cortical activity along the decision axis
COSYNE 2025
Behavioral and histological hallmarks of an intrastriatal rotenone mouse model for Parkinson’s disease
FENS Forum 2024
CD200-based cell sorting generates homogeneous subpopulations of transplantable striatal neuroblasts
FENS Forum 2024
Changes in striatal spiny projection neurons’ properties and circuitry in a mouse model of autism spectrum disorder with cholinergic interneuron dysfunction
FENS Forum 2024
Characterizing the role of movement in ventromedial striatal dopamine signals related to reward
FENS Forum 2024
Convergent regulation of dopamine release by striatal dopamine transporters and GABA receptors
FENS Forum 2024
Corticostriatal overactivity and alpha-synuclein overexpression produce striatal astrocytosis in mice
FENS Forum 2024
Developmental delay in striatal synaptic pruning in lysosomal storage disorders
FENS Forum 2024
Distinct contribution of cortico-striatal mechanisms to elucidate a pathway for conditioned punishment
FENS Forum 2024
Dopamine prediction error signaling in a unique nigrostriatal circuit is critical for associative fear learning
FENS Forum 2024
Effect of RNA m6A methyltransferase activation on anxiety- and depression-related behaviours, monoamine neurochemistry, and striatal gene expression in the rat
FENS Forum 2024
Exercise-based rescue strategies for early striatal synaptic impairment and motor abnormalities caused by alpha-synuclein
FENS Forum 2024
External inputs preferentially drive neurons in the striatal matrix but not striosome
FENS Forum 2024
Extrastriatal dopamine differentially modulates erroneous perceptual confidence
FENS Forum 2024
Fronto-striatal dynamics and optogenetic approaches to remodel impulsive choice
FENS Forum 2024
Functional impairments of striatal neurons in Huntington’s disease: Fast-spiking interneurons and their key role during the early stages of the pathology
FENS Forum 2024
Glucocerebrosidase pharmacological chaperones attenuate α-synuclein-induced neurotoxicity in chronic cortico-striatal slices
FENS Forum 2024
Glycine receptors regulate striatal cholinergic interneurons and dopamine release
FENS Forum 2024
Hippocampal, dorsal striatal, and medial prefrontal cortical computations depend on maze complexity
FENS Forum 2024
Sex hormones-dependent modulation of thalamic inputs to striatal fast-spiking interneurons
FENS Forum 2024
Identification of the striatal molecular landscape in Parkinson’s disease mouse models
FENS Forum 2024
The influence of lateralized retinal stimulation on dopaminergic neuron activity and striatal dopamine release
FENS Forum 2024
Investigating prefronto-striatal circuit dynamics during flexible decision-making
FENS Forum 2024
Laminar distribution pattern and size of crossed corticostriatal neurons in macaques
FENS Forum 2024
Lesion-induced neuroblasts in the striatum are LGE-class interneurons and are not fated towards adult striatal neuron cell types
FENS Forum 2024
Logic of the spatial and functional organization of the cortico-striatal projections onto somatostatin and parvalbumin interneurons in the dorsal striatum of mice
FENS Forum 2024
Modulation of cholinergic interneurons and dopamine release by striatal astrocytes
FENS Forum 2024
MolBoolean staining reveals high proportion of D2 receptors forming A2A-D2 heteromers in striatal neurons of MPTP-lesioned parkinsonian primates
FENS Forum 2024
Morphological alterations of striatal perineuronal nets in a rat model of parkinsonism and levodopa-induced dyskinesias
FENS Forum 2024
Nanoscopic distribution of VAMP2 and VAMP7 in striatal cholinergic varicosities and their respective localization with VAChT and VGLUT3 in synaptic vesicles
FENS Forum 2024