Microcircuit failure in STXBP1 encephalopathy leads to hyperexcitability.

De novo mutations in STXBP1 are among the most prevalent causes of neurodevelopmental disorders and lead to haploinsufficiency, cortical hyperexcitability, epilepsy, and other symptoms in people with mutations. Given that Munc18-1, the protein encoded by STXBP1, is essential for excitatory and inhibitory synaptic transmission, it is currently not understood why mutations cause hyperexcitability. We find that overall inhibition in canonical feedforward microcircuits is defective in a P15-22 mouse model for Stxbp1 haploinsufficiency. Unexpectedly, we find that inhibitory synapses formed by parvalbumin-positive interneurons were largely unaffected. Instead, excitatory synapses fail to recruit inhibitory interneurons. Modeling confirms that defects in the recruitment of inhibitory neurons cause hyperexcitation. CX516, an ampakine that enhances excitatory synapses, restores interneuron recruitment and prevents hyperexcitability. These findings establish deficits in excitatory synapses in microcircuits as a key underlying mechanism for cortical hyperexcitability in a mouse model of Stxbp1 disorder and identify compounds enhancing excitation as a direction for therapy.

Laminar neural dynamics of auditory evoked responses: Computational modeling of local field potentials in auditory cortex of non-human primates.

Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Modeling and simulations provide a way to integrate these different types of information to clarify underlying neural mechanisms. In this study, we aimed to shed light on the neural dynamics underlying auditory evoked responses by fitting a rate-based model to LFPs recorded via multi-contact electrodes which simultaneously sampled neural activity across cortical laminae. Recordings included neural population responses to best-frequency (BF) and non-BF tones at four representative sites in primary auditory cortex (A1) of awake monkeys. The model considered major neural populations of excitatory, parvalbumin-expressing (PV), and somatostatin-expressing (SOM) neurons across layers 2/3, 4, and 5/6. Unknown parameters, including the connection strength between the populations, were fitted to the data. Our results revealed similar population dynamics, fitted model parameters, predicted equivalent current dipoles (ECD), tuning curves, and lateral inhibition profiles across recording sites and animals, in spite of quite different extracellular current distributions. We found that PV firing rates were higher in BF than in non-BF responses, mainly due to different strengths of tonotopic thalamic input, whereas SOM firing rates were higher in non-BF than in BF responses due to lateral inhibition. In conclusion, we demonstrate the feasibility of the model-fitting approach in identifying the contributions of cell-type specific population activity to stimulus-evoked LFPs across cortical laminae, providing a foundation for further investigations into the dynamics of neural circuits underlying cortical sensory processing.

Structural Organization of Perisomatic Inhibition in the Mouse Medial Prefrontal Cortex.

Perisomatic inhibition profoundly controls neural function. However, the structural organization of inhibitory circuits giving rise to the perisomatic inhibition in the higher-order cortices is not completely known. Here, we performed a comprehensive analysis of those GABAergic cells in the medial prefrontal cortex (mPFC) that provide inputs onto the somata and proximal dendrites of pyramidal neurons. Our results show that most GABAergic axonal varicosities contacting the perisomatic region of superficial (layer 2/3) and deep (layer 5) pyramidal cells express parvalbumin (PV) or cannabinoid receptor type 1 (CB1). Further, we found that the ratio of PV/CB1 GABAergic inputs is larger on the somatic membrane surface of pyramidal tract neurons in comparison with those projecting to the contralateral hemisphere. Our morphologic analysis of in vitro labeled PV+ basket cells (PVBC) and CCK/CB1+ basket cells (CCKBC) revealed differences in many features. PVBC dendrites and axons arborized preferentially within the layer where their soma was located. In contrast, the axons of CCKBCs expanded throughout layers, although their dendrites were found preferentially either in superficial or deep layers. Finally, using anterograde trans-synaptic tracing we observed that PVBCs are preferentially innervated by thalamic and basal amygdala afferents in layers 5a and 5b, respectively. Thus, our results suggest that PVBCs can control the local circuit operation in a layer-specific manner via their characteristic arborization, whereas CCKBCs rather provide cross-layer inhibition in the mPFC.SIGNIFICANCE STATEMENT Inhibitory cells in cortical circuits are crucial for the precise control of local network activity. Nevertheless, in higher-order cortical areas that are involved in cognitive functions like decision-making, working memory, and cognitive flexibility, the structural organization of inhibitory cell circuits is not completely understood. In this study we show that perisomatic inhibitory control of excitatory cells in the medial prefrontal cortex is performed by two types of basket cells endowed with different morphologic properties that provide inhibitory inputs with distinct layer specificity on cells projecting to disparate areas. Revealing this difference in innervation strategy of the two basket cell types is a key step toward understanding how they fulfill their distinct roles in cortical network operations.

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy.

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

Retrospective: Patricia S. Goldman-Rakic, pioneer in neuroscience and co-founder of the journal, Cerebral Cortex.

Patricia Goldman-Rakic (1937-2003), the co-founder of this journal, was a pioneering neuroscientist who made transformational discoveries about the prefrontal cortex and the neurobiological basis of working memory. Her research served as the foundation for cognitive neuroscience, and paved the path for women in science. Her multidisciplinary approach created a new paradigm, where the scientific question, rather than a single method, was paramount to the investigation. The current review provides a brief summary of her extraordinary life and scientific contributions.

Cortical interneurons: fit for function and fit to function? Evidence from development and evolution.

Cortical inhibitory interneurons form a broad spectrum of subtypes. This diversity suggests a division of labor, in which each cell type supports a distinct function. In the present era of optimisation-based algorithms, it is tempting to speculate that these functions were the evolutionary or developmental driving force for the spectrum of interneurons we see in the mature mammalian brain. In this study, we evaluated this hypothesis using the two most common interneuron types, parvalbumin (PV) and somatostatin (SST) expressing cells, as examples. PV and SST interneurons control the activity in the cell bodies and the apical dendrites of excitatory pyramidal cells, respectively, due to a combination of anatomical and synaptic properties. But was this compartment-specific inhibition indeed the function for which PV and SST cells originally evolved? Does the compartmental structure of pyramidal cells shape the diversification of PV and SST interneurons over development? To address these questions, we reviewed and reanalyzed publicly available data on the development and evolution of PV and SST interneurons on one hand, and pyramidal cell morphology on the other. These data speak against the idea that the compartment structure of pyramidal cells drove the diversification into PV and SST interneurons. In particular, pyramidal cells mature late, while interneurons are likely committed to a particular fate (PV vs. SST) during early development. Moreover, comparative anatomy and single cell RNA-sequencing data indicate that PV and SST cells, but not the compartment structure of pyramidal cells, existed in the last common ancestor of mammals and reptiles. Specifically, turtle and songbird SST cells also express the Elfn1 and Cbln4 genes that are thought to play a role in compartment-specific inhibition in mammals. PV and SST cells therefore evolved and developed the properties that allow them to provide compartment-specific inhibition before there was selective pressure for this function. This suggest that interneuron diversity originally resulted from a different evolutionary driving force and was only later co-opted for the compartment-specific inhibition it seems to serve in mammals today. Future experiments could further test this idea using our computational reconstruction of ancestral Elfn1 protein sequences.

Thalamic neuromodulation in epilepsy: A primer for emerging circuit-based therapies.

INTRODUCTION: Epilepsy is a common, often debilitating disease of hyperexcitable neural networks. While medically intractable cases may benefit from surgery, there may be no single, well-localized focus for resection or ablation. In such cases, approaching the disease from a network-based perspective may be beneficial. AREAS COVERED: Herein, the authors provide a narrative review of normal thalamic anatomy and physiology and propose general strategies for preventing and/or aborting seizures by modulating this structure. Additionally, they make specific recommendations for targeting the thalamus within different contexts, motivated by a more detailed discussion of its distinct nuclei and their respective connectivity. By describing important principles governing thalamic function and its involvement in seizure networks, the authors aim to provide a primer for those now entering this fast-growing field of thalamic neuromodulation for epilepsy. EXPERT OPINION: The thalamus is critically involved with the function of many cortical and subcortical areas, suggesting it may serve as a compelling node for preventing or aborting seizures, and so it has increasingly been targeted for the surgical treatment of epilepsy. As various thalamic neuromodulation strategies for seizure control are developed, there is a need to ground such interventions in a mechanistic, circuit-based framework.

Accumbal Histamine Signaling Engages Discrete Interneuron Microcircuits.

BACKGROUND: Central histamine (HA) signaling modulates diverse cortical and subcortical circuits throughout the brain, including the nucleus accumbens (NAc). The NAc, a key striatal subregion directing reward-related behavior, expresses diverse HA receptor subtypes that elicit cellular and synaptic plasticity. However, the neuromodulatory capacity of HA within interneuron microcircuits in the NAc remains unknown. METHODS: We combined electrophysiology, pharmacology, voltammetry, and optogenetics in male transgenic reporter mice to determine how HA influences microcircuit motifs controlled by parvalbumin-expressing fast-spiking interneurons (PV-INs) and tonically active cholinergic interneurons (CINs) in the NAc shell. RESULTS: HA enhanced CIN output through an H2 receptor (H2R)-dependent effector pathway requiring Ca2+-activated small-conductance K+ channels, with a small but discernible contribution from H1Rs and synaptic H3Rs. While PV-IN excitability was unaffected by HA, presynaptic H3Rs decreased feedforward drive onto PV-INs via AC-cAMP-PKA (adenylyl cyclase-cyclic adenosine monophosphate-protein kinase A) signaling. H3R-dependent plasticity was differentially expressed at mediodorsal thalamus and prefrontal cortex synapses onto PV-INs, with mediodorsal thalamus synapses undergoing HA-induced long-term depression. These effects triggered downstream shifts in PV-IN- and CIN-controlled microcircuits, including near-complete collapse of mediodorsal thalamus-evoked feedforward inhibition and increased mesoaccumbens dopamine release. CONCLUSIONS: HA targets H1R, H2R, and H3Rs in the NAc shell to engage synapse- and cell type-specific mechanisms that bidirectionally regulate PV-IN and CIN microcircuit activity. These findings extend the current conceptual framework of HA signaling and offer critical insight into the modulatory potential of HA in the brain.

Patterned Duplex Fabric Based on Genetically Modified Spidroin for Smart Wound Management.

The treatment of diabetic wounds remains a great challenge for the medical community. Here, a smart patterned DNA double helix (duplex)-like fabric based on genetically modified spider silk protein (PDF-S) which is inspired by soft plant tendrils, is proposed for diabetic wound treatment. Benefiting from spider silk protein (spidroin); PDF-S is equipped with high strength; high toughness, and excellent biocompatibility. Notably, the fabric crimped through the biomimetic DNA double-helix-like structure can effectively adapt to tensile impact and the maximum stretch rate reaches 1500%. A pattern-based microfluidic channel of PDF-S allowed wound secretion to flow spontaneously through the channel. Meanwhile; due to the optical properties of the introduced photonic crystal structure; PDF-S is equipped with fluorescence enhancement properties; enabling PDF-S to display color-sensitive behavior suitable for wound monitoring and guiding clinical treatment. In addition, to enable sensitive motion monitoring, microelectronic circuits are integrated on the surface of the PDF-S. These unique material features suggest that this study will lead to a new generation of biomimetic artificial spider silk materials for design and application in the biomedical field.

Age-dependent increased sag amplitude in human pyramidal neurons dampens baseline cortical activity.

Aging involves various neurobiological changes, although their effect on brain function in humans remains poorly understood. The growing availability of human neuronal and circuit data provides opportunities for uncovering age-dependent changes of brain networks and for constraining models to predict consequences on brain activity. Here we found increased sag voltage amplitude in human middle temporal gyrus layer 5 pyramidal neurons from older subjects and captured this effect in biophysical models of younger and older pyramidal neurons. We used these models to simulate detailed layer 5 microcircuits and found lower baseline firing in older pyramidal neuron microcircuits, with minimal effect on response. We then validated the predicted reduced baseline firing using extracellular multielectrode recordings from human brain slices of different ages. Our results thus report changes in human pyramidal neuron input integration properties and provide fundamental insights into the neuronal mechanisms of altered cortical excitability and resting-state activity in human aging.

Prefrontal Interneurons: Populations, Pathways, and Plasticity Supporting Typical and Disordered Cognition in Rodent Models.

Prefrontal cortex (PFC) inhibitory microcircuits regulate the gain and timing of pyramidal neuron firing, coordinate neural ensemble interactions, and gate local and long-range neural communication to support adaptive cognition and contextually tuned behavior. Accordingly, perturbations of PFC inhibitory microcircuits are thought to underlie dysregulated cognition and behavior in numerous psychiatric diseases and relevant animal models. This review, based on a Mini-Symposium presented at the 2022 Society for Neuroscience Meeting, highlights recent studies providing novel insights into: (1) discrete medial PFC (mPFC) interneuron populations in the mouse brain; (2) mPFC interneuron connections with, and regulation of, long-range mPFC afferents; and (3) circuit-specific plasticity of mPFC interneurons. The contributions of such populations, pathways, and plasticity to rodent cognition are discussed in the context of stress, reward, motivational conflict, and genetic mutations relevant to psychiatric disease.

Cell-Type Specific Inhibition Controls the High-Frequency Oscillations in the Medial Entorhinal Cortex.

The medial entorhinal cortex (mEC) plays a critical role for spatial navigation and memory. While many studies have investigated the principal neurons within the entorhinal cortex, much less is known about the inhibitory circuitries within this structure. Here, we describe for the first time in the mEC a subset of parvalbumin-positive (PV+) interneurons (INs)-stuttering cells (STUT)-with morphological, intrinsic electrophysiological, and synaptic properties distinct from fast-spiking PV+ INs. In contrast to the fast-spiking PV+ INs, the axon of the STUT INs also terminated in layer 3 and showed subthreshold membrane oscillations at gamma frequencies. Whereas the synaptic output of the STUT INs was only weakly reduced by a µ-opioid agonist, their inhibitory inputs were strongly suppressed. Given these properties, STUT are ideally suited to entrain gamma activity in the pyramidal cell population of the mEC. We propose that activation of the µ-opioid receptors decreases the GABA release from the PV+ INs onto the STUT, resulting in disinhibition of the STUT cell population and the consequent increase in network gamma power. We therefore suggest that the opioid system plays a critical role, mediated by STUT INs, in the neural signaling and oscillatory network activity within the mEC.

In vitro longitudinal lumbar spinal cord preparations to study sensory and recurrent motor microcircuits of juvenile mice.

In vitro spinal cord preparations have been extensively used to study microcircuits involved in the control of movement. By allowing precise control of experimental conditions coupled with state-of-the-art genetics, imaging, and electrophysiological techniques, isolated spinal cords from mice have been an essential tool in detailing the identity, connectivity, and function of spinal networks. The majority of the research has arisen from in vitro spinal cords of neonatal mice, which are still undergoing important postnatal maturation. Studies from adults have been attempted in transverse slices, however, these have been quite challenging due to the poor motoneuron accessibility and viability, as well as the extensive damage to the motoneuron dendritic trees. In this work, we describe two types of coronal spinal cord preparations with either the ventral or the dorsal horn ablated, obtained from mice of different postnatal ages, spanning from preweaned to 1 mo old. These semi-intact preparations allow recordings of sensory-afferent and motor-efferent responses from lumbar motoneurons using whole cell patch-clamp electrophysiology. We provide details of the slicing procedure and discuss the feasibility of whole cell recordings. The in vitro dorsal and ventral horn-ablated spinal cord preparations described here are a useful tool to study spinal motor circuits in young mice that have reached the adult stages of locomotor development.NEW & NOTEWORTHY In the past 20 years, most of the research into the mammalian spinal circuitry has been limited to in vitro preparations from embryonic and neonatal mice. We describe two in vitro longitudinal lumbar spinal cord preparations from juvenile mice that allow the study of motoneuron properties and respective afferent or efferent spinal circuits through whole cell patch clamp. These preparations will be useful to those interested in the study of microcircuits at mature stages of motor development.

Closing the mechanistic gap: the value of microarchitecture in understanding cognitive networks.

Cognitive neuroscience aims to provide biologically relevant accounts of cognition. Contemporary research linking spatial patterns of neural activity to psychological constructs describes 'where' hypothesised functions occur, but not 'how' these regions contribute to cognition. Technological, empirical, and conceptual advances allow this mechanistic gap to be closed by embedding patterns of functional activity in macro- and microscale descriptions of brain organisation. Recent work on the default mode network (DMN) and the multiple demand network (MDN), for example, highlights a microarchitectural landscape that may explain how activity in these networks integrates varied information, thus providing an anatomical foundation that will help to explain how these networks contribute to many different cognitive states. This perspective highlights emerging insights into how microarchitecture can constrain network accounts of human cognition.

Classification of Whisker Deflections From Evoked Responses in the Somatosensory Barrel Cortex With Spiking Neural Networks.

Spike-based neuromorphic hardware has great potential for low-energy brain-machine interfaces, leading to a novel paradigm for neuroprosthetics where spiking neurons in silicon read out and control activity of brain circuits. Neuromorphic processors can receive rich information about brain activity from both spikes and local field potentials (LFPs) recorded by implanted neural probes. However, it was unclear whether spiking neural networks (SNNs) implemented on such devices can effectively process that information. Here, we demonstrate that SNNs can be trained to classify whisker deflections of different amplitudes from evoked responses in a single barrel of the rat somatosensory cortex. We show that the classification performance is comparable or even superior to state-of-the-art machine learning approaches. We find that SNNs are rather insensitive to recorded signal type: both multi-unit spiking activity and LFPs yield similar results, where LFPs from cortical layers III and IV seem better suited than those of deep layers. In addition, no hand-crafted features need to be extracted from the data-multi-unit activity can directly be fed into these networks and a simple event-encoding of LFPs is sufficient for good performance. Furthermore, we find that the performance of SNNs is insensitive to the network state-their performance is similar during UP and DOWN states.

Cerebellar Circuits for Classical Fear Conditioning.

Accumulating evidence indicates that the cerebellum is critically involved in modulating non-motor behaviors, including cognition and emotional processing. Both imaging and lesion studies strongly suggest that the cerebellum is a component of the fear memory network. Given the well-established role of the cerebellum in adaptive prediction of movement and cognition, the cerebellum is likely to be engaged in the prediction of learned threats. The cerebellum is activated by fear learning, and fear learning induces changes at multiple synaptic sites in the cerebellum. Furthermore, recent technological advances have enabled the investigation of causal relationships between intra- and extra-cerebellar circuits and fear-related behaviors such as freezing. Here, we review the literature on the mechanisms underlying the modulation of cerebellar circuits in a mammalian brain by fear conditioning at the cellular and synaptic levels to elucidate the contributions of distinct cerebellar structures to fear learning and memory. This knowledge may facilitate a deeper understanding and development of more effective treatment strategies for fear-related affective disorders including post-traumatic stress or anxiety related disorders.

Modular microcircuit organization of the presubicular head-direction map.

Our internal sense of direction is thought to rely on the activity of head-direction (HD) neurons. We find that the mouse dorsal presubiculum (PreS), a key structure in the cortical representation of HD, displays a modular "patch-matrix" organization, which is conserved across species (including human). Calbindin-positive layer 2 neurons within the "matrix" form modular recurrent microcircuits, while inputs from the anterodorsal and laterodorsal thalamic nuclei are non-overlapping and target the "patch" and "matrix" compartments, respectively. The apical dendrites of identified HD cells are largely restricted within the "matrix," pointing to a non-random sampling of patterned inputs and to a precise structure-function architecture. Optogenetic perturbation of modular recurrent microcircuits results in a drastic tonic suppression of firing only in a subpopulation of HD neurons. Altogether, our data reveal a modular microcircuit organization of the PreS HD map and point to the existence of cell-type-specific microcircuits that support the cortical HD representation.

Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits.

Cortical processing depends on finely tuned excitatory and inhibitory connections in neuronal microcircuits. Reduced inhibition by somatostatin-expressing interneurons is a key component of altered inhibition associated with treatment-resistant major depressive disorder (depression), which is implicated in cognitive deficits and rumination, but the link remains to be better established mechanistically in humans. Here we test the effect of reduced somatostatin interneuron-mediated inhibition on cortical processing in human neuronal microcircuits using a data-driven computational approach. We integrate human cellular, circuit, and gene expression data to generate detailed models of human cortical microcircuits in health and depression. We simulate microcircuit baseline and response activity and find a reduced signal-to-noise ratio and increased false/failed detection of stimuli due to a higher baseline activity in depression. We thus apply models of human cortical microcircuits to demonstrate mechanistically how reduced inhibition impairs cortical processing in depression, providing quantitative links between altered inhibition and cognitive deficits.

Microcircuits for spatial coding in the medial entorhinal cortex.

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.

Dimensionality reduction and recurrence analysis reveal hidden structures of striatal pathological states.

A pipeline is proposed here to describe different features to study brain microcircuits on a histological scale using multi-scale analyses, including the uniform manifold approximation and projection (UMAP) dimensional reduction technique and modularity algorithm to identify neuronal ensembles, Runs tests to show significant ensembles activation, graph theory to show trajectories between ensembles, and recurrence analyses to describe how regular or chaotic ensembles dynamics are. The data set includes ex-vivo NMDA-activated striatal tissue in control conditions as well as experimental models of disease states: decorticated, dopamine depleted, and L-DOPA-induced dyskinetic rodent samples. The goal was to separate neuronal ensembles that have correlated activity patterns. The pipeline allows for the demonstration of differences between disease states in a brain slice. First, the ensembles were projected in distinctive locations in the UMAP space. Second, graphs revealed functional connectivity between neurons comprising neuronal ensembles. Third, the Runs test detected significant peaks of coactivity within neuronal ensembles. Fourth, significant peaks of coactivity were used to show activity transitions between ensembles, revealing recurrent temporal sequences between them. Fifth, recurrence analysis shows how deterministic, chaotic, or recurrent these circuits are. We found that all revealed circuits had recurrent activity except for the decorticated circuits, which tended to be divergent and chaotic. The Parkinsonian circuits exhibit fewer transitions, becoming rigid and deterministic, exhibiting a predominant temporal sequence that disrupts transitions found in the controls, thus resembling the clinical signs of rigidity and paucity of movements. Dyskinetic circuits display a higher recurrence rate between neuronal ensembles transitions, paralleling clinical findings: enhancement in involuntary movements. These findings confirm that looking at neuronal circuits at the histological scale, recording dozens of neurons simultaneously, can show clear differences between control and diseased striatal states: "fingerprints" of the disease states. Therefore, the present analysis is coherent with previous ones of striatal disease states, showing that data obtained from the tissue are robust. At the same time, it adds heuristic ways to interpret circuitry activity in different states.