Thalamic input to motor cortex facilitates goal-directed action initiation

The plasticity of pyramidal neurons in the behaving brain

Neurons are plastic. That is, they change their activity according to different behavioural conditions. This endows pyramidal neurons with an incredible computational power for the integration and processing of synaptic inputs. Plasticity can be investigated at different levels of investigation within a single neuron, from spines to dendrites, to synaptic input. Although most of our knowledge stems from the in vitro brain slice preparation, plasticity plays a vital role during behaviour by providing a flexible substrate for the execution of appropriate actions in our ever-changing environment. Owing to advances in recording techniques, the plasticity of neurons and the neural networks in which they are embedded is now beginning to be realized in the in vivo intact brain. This review focuses on the structural and functional synaptic plasticity of pyramidal neurons, with a specific focus on the latest developments from in vivo studies. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Casual associations between brain structure and sarcopenia: A large-scale genetic correlation and mendelian randomization study

Sarcopenia presenting a critical challenge in population-aging healthcare. The elucidation of the interplay between brain structure and sarcopenia necessitates further research. The aim of this study is to explore the casual association between brain structure and sarcopenia. Linkage disequilibrium score regression (LDSC) was conducted to estimate the genetic correlations; MR was then performed to explore the causal relationship between Brain imaging-derived phenotypes (BIDPs) and three sarcopenia-related traits: handgrip strength, walking pace, and appendicular lean mass (ALM). The main analyses were conducted using the inverse-variance weighted method. Moreover, weighted median and MR-Egger were conducted as sensitivity analyses. Genetic association between 6.41% of BIDPs and ALM was observed, and 4.68% of BIDPs exhibited causal MR association with handgrip strength, 2.11% of BIDPs were causally associated with walking pace, and 2.04% of BIDPs showed causal association with ALM. Volume of ventromedial hypothalamus was associated with increased odds of handgrip strength (OR: 1.18, 95% CI: 1.02 to 1.37) and ALM (OR: 1.05, 95% CI: 1.01 to 1.09). Mean thickness of G-pariet-inf-Angular was associated with decreased odds of handgrip strength (OR: 0.83, 95% CI: 0.70 to 0.97) and walking pace (OR: 0.97, 95% CI: 0.93 to 0.99). As part of the brain structure forward causally influences sarcopenia, which may provide new perspectives for the prevention of sarcopenia and offer valuable insights for further research on the brain-muscle axis.

FABEL: Forecasting Animal Behavioral Events with Deep Learning-Based Computer Vision

Behavioral neuroscience aims to provide a connection between neural phenomena and emergent organism-level behaviors. This requires perturbing the nervous system and observing behavioral outcomes, and comparing observed post-perturbation behavior with predicted counterfactual behavior and therefore accurate behavioral forecasts. In this study we present FABEL, a deep learning method for forecasting future animal behaviors and locomotion trajectories from historical locomotion alone. We train an offline pose estimation network to predict animal body-part locations in behavioral video; then sequences of pose vectors are input to deep learning time-series forecasting models. Specifically, we train an LSTM network that predicts a future food interaction event in a specified time window, and a Temporal Fusion Transformer that predicts future trajectories of animal body-parts, which are then converted into probabilistic label forecasts. Importantly, accurate prediction of food interaction provides a basis for neurobehavioral intervention in the context of compulsive eating. We show promising results on forecasting tasks between 100 milliseconds and 5 seconds timescales. Because the model takes only behavioral video as input, it can be adapted to any behavioral task and does not require specific physiological readouts. Simultaneously, these deep learning models may serve as extensible modules that can accommodate diverse signals, such as in-vivo fluorescence imaging and electrophysiology, which may improve behavior forecasts and elucidate invervention targets for desired behavioral change.

Synaptic plasticity in human thalamocortical assembloids

Synaptic plasticities, such as long-term potentiation (LTP) and depression (LTD), tune synaptic efficacy and are essential for learning and memory. Current studies of synaptic plasticity in humans are limited by a lack of adequate human models. Here, we modeled the thalamocortical system by fusing human induced pluripotent stem cell-derived thalamic and cortical organoids. Single-nucleus RNA-sequencing revealed that most cells in mature thalamic organoids were glutamatergic neurons. When fused to form thalamocortical assembloids, thalamic and cortical organoids formed reciprocal long-range axonal projections and reciprocal synapses detectable by light and electron microscopy, respectively. Using whole-cell patch-clamp electrophysiology and two-photon imaging, we characterized glutamatergic synaptic transmission. Thalamocortical and corticothalamic synapses displayed short-term plasticity analogous to that in animal models. LTP and LTD were reliably induced at both synapses; however, their mechanisms differed from those previously described in rodents. Thus, thalamocortical assembloids provide a model system for exploring synaptic plasticity in human circuits.

Modeling Synaptic Integration of Bursty and β Oscillatory Inputs in Ventromedial Motor Thalamic Neurons in Normal and Parkinsonian States

The ventromedial motor thalamus (VM) is implicated in multiple motor functions and occupies a central position in the cortico-basal ganglia-thalamocortical loop. It integrates glutamatergic inputs from motor cortex (MC) and motor-related subcortical areas, and it is a major recipient of inhibition from basal ganglia. Previous in vitro experiments performed in mice showed that dopamine depletion enhances the excitability of thalamocortical (TC) neurons in VM due to reduced M-type potassium currents. To understand how these excitability changes impact synaptic integration in vivo, we constructed biophysically detailed mouse VM TC model neurons fit to normal and dopamine-depleted conditions, using the NEURON simulator. These models allowed us to assess the influence of excitability changes with dopamine depletion on the integration of synaptic inputs expected in vivo We found that VM neuron models in the dopamine-depleted state showed increased firing rates with the same synaptic inputs. Synchronous bursting in inhibitory input from the substantia nigra pars reticulata (SNR), as observed in parkinsonian conditions, evoked a postinhibitory firing rate increase with a longer duration in dopamine-depleted than control conditions, due to different M-type potassium channel densities. With β oscillations in the inhibitory inputs from SNR and the excitatory inputs from cortex, we observed spike-phase locking in the activity of the models in normal and dopamine-depleted states, which relayed and amplified the oscillations of the inputs, suggesting that the increased β oscillations observed in VM of parkinsonian animals are predominantly a consequence of changes in the presynaptic activity rather than changes in intrinsic properties.

A thalamocortical pathway controlling impulsive behavior

Planning and anticipating motor actions enables movements to be quickly and accurately executed. However, if anticipation is not properly controlled, it can lead to premature impulsive actions. Impulsive behavior is defined as actions that are poorly conceived and are often risky and inappropriate. Historically, impulsive behavior was thought to be primarily controlled by the frontal cortex and basal ganglia. More recently, two additional brain regions, the ventromedial (VM) thalamus and the anterior lateral motor cortex (ALM), have been shown to have an important role in mice. Here, we explore this newly discovered role of the thalamocortical pathway and suggest cellular mechanisms that may be involved in driving the cortical activity that contributes to impulsive behavior.

Whole-brain monosynaptic inputs to lateral periaqueductal gray glutamatergic neurons in mice

OBJECTIVE

The lateral periaqueductal gray (LPAG), which mainly contains glutamatergic neurons, plays an important role in social responses, pain, and offensive and defensive behaviors. Currently, the whole-brain monosynaptic inputs to LPAG glutamatergic neurons are unknown. This study aims to explore the structural framework of the underlying neural mechanisms of LPAG glutamatergic neurons.

METHODS

This study used retrograde tracing systems based on the rabies virus, Cre-LoxP technology, and immunofluorescence analysis.

RESULTS

We found that 59 nuclei projected monosynaptic inputs to the LPAG glutamatergic neurons. In addition, seven hypothalamic nuclei, namely the lateral hypothalamic area (LH), lateral preoptic area (LPO), substantia innominata (SI), medial preoptic area, ventral pallidum, posterior hypothalamic area, and lateral globus pallidus, projected most densely to the LPAG glutamatergic neurons. Notably, we discovered through further immunofluorescence analysis that the inputs to the LPAG glutamatergic neurons were colocalized with several markers related to important neurological functions associated with physiological behaviors.

CONCLUSION

The LPAG glutamatergic neurons received dense projections from the hypothalamus, especially nuclei such as LH, LPO, and SI. The input neurons were colocalized with several markers of physiological behaviors, which show the pivotal role of glutamatergic neurons in the physiological behaviors regulation by LPAG.

Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment

Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.

Reduced thalamic excitation to motor cortical pyramidal tract neurons in parkinsonism

Degeneration of midbrain dopaminergic (DA) neurons alters the connectivity and functionality of the basal ganglia-thalamocortical circuits in Parkinson's disease (PD). Particularly, the aberrant outputs of the primary motor cortex (M1) contribute to parkinsonian motor deficits. However, cortical adaptations at cellular and synaptic levels in parkinsonism remain poorly understood. Using multidisciplinary approaches, we found that DA degeneration induces cell subtype- and input-specific reduction of thalamic excitation to M1 pyramidal tract (PT) neurons. At molecular level, we identified that N-methyl-d-aspartate (NMDA) receptors play a key role in mediating the reduced thalamocortical excitation to PT neurons. At circuit level, we showed that the reduced thalamocortical transmission in parkinsonian mice can be rescued by chemogenetically suppressing basal ganglia outputs. Together, our data suggest that cell subtype- and synapse-specific adaptations in M1 contribute to altered cortical outputs in parkinsonism and are important aspects of PD pathophysiology.

Toward a cerebello-thalamo-cortical computational model of spinocerebellar ataxia

Computational neural network modelling is an emerging approach for optimization of drug treatment of neurological disorders and fine-tuning of rehabilitation strategies. In the current study, we constructed a cerebello-thalamo-cortical computational neural network model to simulate a mouse model of cerebellar ataxia (pcd^5J mice) by manipulating cerebellar bursts through reduction of GABAergic inhibitory input. Cerebellar output neurons were projected to the thalamus and bidirectionally connected with the cortical network. Our results showed that reduction of inhibitory input in the cerebellum orchestrated the cortical local field potential (LFP) dynamics to generate specific motor outputs of oscillations of the theta, alpha, and beta bands in the computational model as well as in mouse motor cortical neurons. The therapeutic potential of deep brain stimulation (DBS) was tested in the computational model by increasing the sensory input to restore cortical output. Ataxia mice showed normalization of the motor cortex LFP after cerebellum DBS. We provide a novel approach to computational modelling to investigate the effect of DBS by mimicking cerebellar ataxia involving degeneration of Purkinje cells. Simulated neural activity coincides with findings from neural recordings of ataxia mice. Our computational model could thus represent cerebellar pathologies and provide insight into how to improve disease symptoms by restoring neuronal electrophysiological properties using DBS.

Neural basis of anticipation and premature impulsive action in the frontal cortex

Planning motor actions can improve behavioral performance; however, it can also lead to premature actions. Although the anterior lateral motor cortex (ALM) is known to be important for correct motor planning, it is currently unknown how it contributes to premature impulsive motor output. This was addressed using whole-cell voltage recordings from layer 2/3 pyramidal neurons within the ALM while mice performed a cued sensory association task. Here, a robust voltage response was evoked during the auditory cue, which was greater during incorrect premature behavior than during correct performance in the task. Optogenetically suppressing ALM during the cued sensory association task led to enhanced behavior, with fewer, and more delayed, premature responses and faster correct responses. Taken together, our findings extend the current known roles of the ALM, illustrating that ALM plays an important role in impulsive behavior by encoding and influencing premature motor output.

Thalamus-driven functional populations in frontal cortex support decision-making

Neurons in frontal cortex exhibit diverse selectivity representing sensory, motor and cognitive variables during decision-making. The neural circuit basis for this complex selectivity remains unclear. We examined activity mediating a tactile decision in mouse anterior lateral motor cortex in relation to the underlying circuits. Contrary to the notion of randomly mixed selectivity, an analysis of 20,000 neurons revealed organized activity coding behavior. Individual neurons exhibited prototypical response profiles that were repeatable across mice. Stimulus, choice and action were coded nonrandomly by distinct neuronal populations that could be delineated by their response profiles. We related distinct selectivity to long-range inputs from somatosensory cortex, contralateral anterior lateral motor cortex and thalamus. Each input connects to all functional populations but with differing strength. Task selectivity was more strongly dependent on thalamic inputs than cortico-cortical inputs. Our results suggest that the thalamus drives subnetworks within frontal cortex coding distinct features of decision-making.

Frontal cortex contains a complex mixture of signals reflecting distinct behavioral and cognitive processes. An analysis of 20,000 neurons during decision-making revealed distinct functional clusters and their activities are driven by the thalamus.

Voluntary Motor Command Release Coincides with Restricted Sensorimotor Beta Rhythm Phases

Sensory perception and memory are enhanced during restricted phases of ongoing brain rhythms, but whether voluntary movement is constrained by brain rhythm phase is not known. Voluntary movement requires motor commands to be released from motor cortex (M1) and transmitted to spinal motoneurons and effector muscles. Here, we tested the hypothesis that motor commands are preferentially released from M1 during circumscribed phases of ongoing sensorimotor rhythms. Healthy humans of both sexes performed a self-paced finger movement task during electroencephalography (EEG) and electromyography (EMG) recordings. We first estimated the time of motor command release preceding each finger movement by subtracting individually measured corticomuscular transmission latencies from EMG-determined movement onset times. Then, we determined the phase of ipsilateral and contralateral sensorimotor mu (8-12 Hz) and beta (13-35 Hz) rhythms during release of each motor command. We report that motor commands were most often released between 120 and 140° along the contralateral beta cycle but were released uniformly along the contralateral mu cycle. Motor commands were also released uniformly along ipsilateral mu and beta cycles. Results demonstrate that motor command release coincides with restricted phases of the contralateral sensorimotor beta rhythm, suggesting that sensorimotor beta rhythm phase may sculpt the timing of voluntary human movement.SIGNIFICANCE STATEMENT Perceptual and cognitive function is optimal during specific brain rhythm phases. Although brain rhythm phase influences motor cortical neuronal activity and communication between the motor cortex and spinal cord, its role in voluntary movement is poorly understood. Here, we show that the motor commands needed to produce voluntary movements are preferentially released from the motor cortex during contralateral sensorimotor beta rhythm phases. Our findings are consistent with the notion that sensorimotor rhythm phase influences the timing of voluntary human movement.

Neural Algorithms and Circuits for Motor Planning

The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

Where Actions Meet Outcomes: Medial Prefrontal Cortex, Central Thalamus, and the Basal Ganglia

Medial prefrontal cortex (mPFC) interacts with distributed networks that give rise to goal-directed behavior through afferent and efferent connections with multiple thalamic nuclei and recurrent basal ganglia-thalamocortical circuits. Recent studies have revealed individual roles for different thalamic nuclei: mediodorsal (MD) regulation of signaling properties in mPFC neurons, intralaminar control of cortico-basal ganglia networks, ventral medial facilitation of integrative motor function, and hippocampal functions supported by ventral midline and anterior nuclei. Large scale mapping studies have identified functionally distinct cortico-basal ganglia-thalamocortical subnetworks that provide a structural basis for understanding information processing and functional heterogeneity within the basal ganglia. Behavioral analyses comparing functional deficits produced by lesions or inactivation of specific thalamic nuclei or subregions of mPFC or the basal ganglia have elucidated the interdependent roles of these areas in adaptive goal-directed behavior. Electrophysiological recordings of mPFC neurons in rats performing delayed non-matching-to position (DNMTP) and other complex decision making tasks have revealed populations of neurons with activity related to actions and outcomes that underlie these behaviors. These include responses related to motor preparation, instrumental actions, movement, anticipation and delivery of action outcomes, memory delay, and spatial context. Comparison of results for mPFC, MD, and ventral pallidum (VP) suggest critical roles for mPFC in prospective processes that precede actions, MD for reinforcing task-relevant responses in mPFC, and VP for providing feedback about action outcomes. Synthesis of electrophysiological and behavioral results indicates that different networks connecting mPFC with thalamus and the basal ganglia are organized to support distinct functions that allow organisms to act efficiently to obtain intended outcomes.

Reexperiencing and anxious arousal symptoms in relation to volumes of thalamus nuclei in posttraumatic stress spectrum adults

INTRODUCTION

Trauma reexperiencing is dominated by recollection of sensory-perceptual elements of the trauma, pointing to involvement of the sensory thalamus. This study examined posttraumatic stress symptoms in relation to volumes of thalamic nuclei that were grouped based on their predominant functions. We hypothesized that reexperiencing, controlling for other symptom dimensions, would correlate with volumes of thalamic nuclei involved in primary and higher-order sensory processing.

METHODS

Seventy-two trauma-exposed adults were interviewed with the Clinician Administered PTSD Scale for DSM-IV and underwent 3T magnetic resonance imaging. Scores were derived for reexperiencing, anxious arousal, dysphoric arousal, emotional numbing, and avoidance symptoms. These were entered as simultaneous predictors in five separate regression analyses, with age, sex, and total thalamus volume as covariates, predicting volumesf of five thalamus nuclear groupings corrected for intracranial volume: Specific sensory, associative-sensory, associative-cognitive, intralaminar, and motor groupings.

RESULTS

Reexperiencing symptoms were significantly positively correlated with volumes of the motor thalamic grouping, which included the ventral anterior, ventral lateral, and ventromedial nuclei. Anxious arousal was significantly negatively correlated with volumes of all five thalamic groupings.

CONCLUSIONS

Reexperiencing symptoms were correlated with volumes of the motor thalamus, while anxious arousal symptoms were related to all thalamic subregion volumes. Thalamic nuclei involved in motor functions, including oculomotor control and motor planning, may be implicated in posttraumatic reexperiencing symptoms.

A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement

Motor behaviors are often planned long before execution but only released after specific sensory events. Planning and execution are each associated with distinct patterns of motor cortex activity. Key questions are how these dynamic activity patterns are generated and how they relate to behavior. Here, we investigate the multi-regional neural circuits that link an auditory "Go cue" and the transition from planning to execution of directional licking. Ascending glutamatergic neurons in the midbrain reticular and pedunculopontine nuclei show short latency and phasic changes in spike rate that are selective for the Go cue. This signal is transmitted via the thalamus to the motor cortex, where it triggers a rapid reorganization of motor cortex state from planning-related activity to a motor command, which in turn drives appropriate movement. Our studies show how midbrain can control cortical dynamics via the thalamus for rapid and precise motor behavior.

The role of higher order thalamus during learning and correct performance in goal-directed behavior

The thalamus is a gateway to the cortex. Cortical encoding of complex behavior can therefore only be understood by considering the thalamic processing of sensory and internally generated information. Here, we use two-photon Ca²⁺ imaging and optogenetics to investigate the role of axonal projections from the posteromedial nucleus of the thalamus (POm) to the forepaw area of the mouse primary somatosensory cortex (forepaw S1). By recording the activity of POm axonal projections within forepaw S1 during expert and chance performance in two tactile goal-directed tasks, we demonstrate that POm axons increase activity in the response and, to a lesser extent, reward epochs specifically during correct HIT performance. When performing at chance level during learning of a new behavior, POm axonal activity was decreased to naive rates and did not correlate with task performance. However, once evoked, the Ca²⁺ transients were larger than during expert performance, suggesting POm input to S1 differentially encodes chance and expert performance. Furthermore, the POm influences goal-directed behavior, as photoinactivation of archaerhodopsin-expressing neurons in the POm decreased the learning rate and overall success in the behavioral task. Taken together, these findings expand the known roles of the higher-thalamic nuclei, illustrating the POm encodes and influences correct action during learning and performance in a sensory-based goal-directed behavior.

Input rate encoding and gain control in dendrites of neocortical pyramidal neurons

Elucidating how neurons encode network activity is essential to understanding how the brain processes information. Neocortical pyramidal cells receive excitatory input onto spines distributed along dendritic branches. Local dendritic branch nonlinearities can boost the response to spatially clustered and synchronous input, but how this translates into the integration of patterns of ongoing activity remains unclear. To examine dendritic integration under naturalistic stimulus regimes, we use two-photon glutamate uncaging to repeatedly activate multiple dendritic spines at random intervals. In the proximal dendrites of two populations of layer 5 pyramidal neurons in the mouse motor cortex, spatially restricted synchrony is not a prerequisite for dendritic boosting. Branches encode afferent inputs with distinct rate sensitivities depending upon cell and branch type. Thus, inputs distributed along a dendritic branch can recruit supralinear boosting and the window of this nonlinearity may provide a mechanism by which dendrites can preferentially amplify slow-frequency network oscillations.