bioRxiv Subject Collection: Neuroscience's Journal

Dynamic changes in neuronal and glial GAL4 driver expression during Drosophila ageing
Understanding how diverse cell types come together to form a functioning brain relies on the ability to specifically target these cells. This is often done using genetic tools such as the GAL4/UAS system in Drosophila melanogaster. Surprisingly, despite its extensive usage during studies of the ageing brain, detailed spatio-temporal characterisation of GAL4 driver lines in adult flies has been lacking. Here we show that three commonly used neuronal drivers (elav[C155]-GAL4, nSyb[R57C10]-GAL4 and ChAT-GAL4) and the commonly used glial driver repo-GAL4 all show rapid and pronounced decreases in activity over the first 1.5 weeks of adult life, with activity becoming undetectable in some regions after 30 days. In addition to an overall decrease in GAL4 activity over time, we found notable differences in spatial patterns, mostly occurring soon after eclosion. Although all lines showed these changes, the nSyb-GAL4 line exhibited the most consistent and stable expression patterns over ageing. Our findings suggest that gene transcription of key loci decreases in the aged brain, a finding broadly similar to previous work in mammalian brains. Our results also raise questions over past work on long-term expression of disease models in the brain, and stress the need to find better genetic tools for ageing studies.

Co-Contraction Embodies Uncertainty: An Optimal Feedforward Strategy for Robust Motor Control
Despite our environment is often uncertain, we generally manage to generate stable motor behaviors. While reactive control plays a major role in this achievement, proactive control is critical to cope with the substantial noise and delays that affect neuromusculoskeletal systems. In particular, muscle co-contraction is exploited to robustify feedforward motor commands against internal sensorimotor noise as was revealed by stochastic optimal open-loop control modeling. Here, we extend this framework to neuromusculoskeletal systems subjected to random disturbances originating from the environment. The analytical derivation and numerical simulations predict a singular relationship between the degree of uncertainty in the task at hand and the optimal level of anticipatory co-contraction. This prediction is confirmed through a single-joint pointing task experiment where an external torque is applied to the wrist near the end of the reaching movement with varying probabilities across blocks of trials. We conclude that uncertainty calls for impedance control via proactive muscle co-contraction to stabilize behaviors when reactive control is insufficient for task success.

Densely sampled stimulus-response map of human cortex with single pulse TMS-EEG and its relation to whole brain neuroimaging measures
Large-scale networks underpin brain functions. How such networks respond to focal stimulation can help decipher complex brain processes and optimize brain stimulation treatments. To map such stimulation-response patterns across the brain non-invasively, we recorded concurrent EEG responses from single-pulse transcranial magnetic stimulation (i.e., TMS-EEG) from over 100 cortical regions with two orthogonal coil orientations from one densely-sampled individual. We also acquired Human Connectome Project (HCP)-styled diffusion imaging scans (six), resting-state functional Magnetic Resonance Imaging (fMRI) scans (120 mins), resting-state EEG scans (108 mins), and structural MR scans (T1- and T2-weighted). Using the TMS-EEG data, we applied network science-based community detection to reveal insights about the brain's causal-functional organization from both a stimulation and recording perspective. We also computed structural and functional maps and the electric field of each TMS stimulation condition. Altogether, we hope the release of this densely sampled (n=1) dataset will be a uniquely valuable resource for both basic and clinical neuroscience research.

How the brain learns to parse images using an attentional, incremental grouping process
Natural scenes usually contain a vast number of objects that need to be segmented and segregated from each other and from the background to guide behaviour. In the visual brain, object-based attention is the process by which image fragments belonging to the same objects are grouped together. The curve-tracing task is a special case of a perceptual grouping task that tests our ability to group image elements of an elongated curve. The task consists in determining which image elements belong to the same curve, and in the brain, neurons spread an enhanced activity level over the representation of the relevant curve. A previous "growth-cone model of attention" accounted for the scale invariance of tracing by proposing that the enhanced activity propagates at multiple levels of the visual cortical hierarchy. However, the precise neuronal circuitry for learning and implementing scale-invariant tracing remains unknown. We propose a new recurrent architecture for the scale-invariant labelling of curves and objects. The architecture is composed of a feedforward pathway that dynamically selects the right scale and prevents the spilling over of the enhanced activity to other curves, and a recurrent pathway for tag spreading that involves horizontal and feedback interactions, mediated by a disinhibitory loop involving VIP and SOM interneurons. We trained the network with curves up to seven pixels long using reinforcement learning and a learning rule local in time and space and we found that it generalized to curves of any length and to spatially extended objects. The network chose the appropriate scale and switched to higher or lower scales as dictated by the distance between curves, just has as been observed in human psychophysics and in the visual cortex of monkeys. Our work provide a mechanistic account of the learning of scale-invariant perceptual grouping in the brain.

Molecular characterization of gustatory second-order neurons reveals integrative mechanisms of gustatory and metabolic information
Animals must balance the urgent need to find food during starvation with the critical necessity to avoid toxic substances to ensure their survival. In Drosophila, specialized Gustatory Receptors (GRs) expressed in Gustatory Receptor Neurons (GRNs) are critical for distinguishing between nutritious and potentially toxic food. GRNs project their axons from taste organs to the Subesophageal Zone (SEZ) in the Central Brain (CB) of Drosophila, where gustatory information is processed. Although the roles of GRs and GRNs are well-documented, the processing of gustatory information in the SEZ remains unclear. To better understand gustatory sensory processing and feeding decision-making, we molecularly characterized the first layer of gustatory interneurons, referred to as Gustatory Second Order Neurons (G2Ns), which receive direct input from GRNs. Using trans-synaptic tracing with trans-Tango, cell sorting, and bulk RNAseq under fed and starved conditions, we discovered that G2Ns vary based on gustatory input and that their molecular profile changes with the fly's metabolic state. Further data analysis has revealed that a pair of neurons in the SEZ, expressing the neuropeptide Leucokinin (SELK neurons), receive simultaneous input from GRNs sensing bitter (potentially toxic) and sweet (nutritious) information. Additionally, these neurons also receive inputs regarding the starvation levels of the fly. These results highlight a novel mechanism of feeding regulation and metabolic integration.

Lateral entorhinal cortex afferents reconfigure the activity in piriform cortex circuits
Odours are key signals for guiding spatial behaviours such as foraging and navigation in rodents. It has recently been found that odour representations in the piriform cortex (PCx) can also contain information about their spatial context. However, the precise origins of this information within the brain and its subsequent integration into the microcircuitry of the PCx remains unknown. In this study, we focus on the lateral entorhinal cortex (LEC) as a candidate for carrying spatial contextual information to the PCx, to investigate how it affects the PCx microcircuit and its response to olfactory inputs. Utilising mice brain slices, we performed patch clamp recordings targeting both superficial (SP) and deep (DP) pyramidal neurons, as well as parvalbumin (PV) and somatostatin (SOM) inhibitory interneurons. Concurrently, we optogenetically stimulated excitatory LEC projections to study their impact on PCx activity. We found that LEC inputs are heterogeneously distributed in the PCx microcircuit, evoking larger excitatory currents in SP and PV neurons compared to DP and SOM neurons, respectively, due to their higher monosynaptic connectivity. Moreover, LEC inputs exert a differential effect on the inhibitory circuits, activating PV while suppressing SOM interneurons. We further studied the interaction among LEC inputs and the sensory afferent signals originating from the lateral olfactory tract (LOT) onto the PCx. Our findings demonstrated that both SP and DP neurons show a general increase in their spiking response when LEC and LOT are simultaneously activated. Notably, DP neurons exhibit a sharpening of their response attributable to LEC-induced inhibition that effectively suppresses the delayed spikes evoked by LOT stimulation. These observations suggest a regulatory mechanism whereby LEC inputs inhibit recurrent activity by activating PV interneurons. Our results show that LEC afferents reconfigure PCx activity and contribute to the understanding of how odour objects are formed within the PCx integrating both olfactory and contextual information.

Functional Control of Network Dynamical Systems: An Information Theoretic Approach
In neurological networks, the emergence of various causal interactions and information flows among nodes is governed by the structural connectivity in conjunction with the node dynamics. The information flow describes the direction and the magnitude of an excitatory neuron's influence to the neighbouring neurons. However, the intricate relationship between network dynamics and information flows is not well understood. Here, we address this challenge by first identifying a generic mechanism that defines the evolution of various information routing patterns in response to modifications in the underlying network dynamics. Moreover, with emerging techniques in brain stimulation, designing optimal stimulation directed towards a target region with an acceptable magnitude remains an ongoing and significant challenge. In this work, we also introduce techniques for computing optimal inputs that follow a desired stimulation routing path towards the target brain region. This optimization problem can be efficiently resolved using non-linear programming tools and permits the simultaneous assignment of multiple desired patterns at different instances. We establish the algebraic and graph-theoretic conditions necessary to ensure the feasibility and stability of information routing patterns (IRPs). We illustrate the routing mechanisms and control methods for attaining desired patterns in biological oscillatory dynamics.

Metabolic connectivity in ageing.
Information transfer across the brain has a high energetic cost and requires the efficient use of glucose. Positron emission tomography (PET) studies have shown that ageing is associated with a decline in regional rates of cerebral glucose metabolism. However, until recently, it has not been possible to measure the timecourse of molecular activity within an individual using PET, preventing the study of metabolic network connectivity across the brain. Here we report the results of the first high temporal resolution functional PET study examining metabolic connectivity and cognitive function in ageing. The metabolic connectomes of 40 younger (mean age 27.9 years; range 20-42) and 46 older (mean 75.8; 60-89) adults were characterised by high connectivity strength in the frontal, temporal, motor, parietal and medial cortices. Ageing was associated with lower global integration of metabolic hub regions, indicating disrupted information transfer across the metabolic network in older adults. In younger adults, a high proportion of glucose was used to support hubs in the frontal regions. Older adults had a smaller energy budget in comparison to younger adults, and older adults used a higher proportion of energy to support mostly posterior hub regions. This difference in the metabolic network topology in older adults was associated with worse cognitive performance. We conclude that ageing is associated with reduced metabolic connectivity, an altered metabolic network topology and a high glucose cost in hub regions. Our results highlight the fundamental role that metabolism plays in supporting information transfer in the brain and the unique insights that metabolic connectivity provides into the ageing brain.

Low-dimensional olfactory signatures of fruit ripening and fermentation
Odors provide an important communication channel between plants and animals. Fruits, vital nutrient sources for animals, emit a complex array of monomolecular volatiles. Animals can use the structure of these mixtures to assess properties of fruit predictive of their nutritive and reproductive value. We analyzed the statistics of fruit odor mixtures sampled across stages of ripening and fermentation to find that they fall on a low-dimensional hyperbolic map. Hyperbolic maps, with their negative curvature and an exponentially expanding state options, are adept at describing hierarchical relationships in the data such as those arising from metabolic processes within fruits. In the hyperbolic map, samples followed a striking spiral trajectory. The spiral initiated near the maps core, representing the under-ripe phase with specific profiles of monomolecular volatiles. Progressively mapping along the unfolding spiral trajectory were scent mixtures corresponding to ripening, and then rotting or fermentation. The unfolding process depended on the specific fermentation processes that dominated in the samples, determined largely by the microbes (e.g. bacteria or yeast) present in the sample. These results generalized across fruit types and describe trajectories in the natural odorant space with significant behavioral relevance for insects.

CHD8 adulthood microglial knockout induces behavioral, morphological, and transcriptional changes in a sex-dependent manner
Mutations in CHD8 (chromodomain-helicase-DNA binding protein 8) are highly associated with autism spectrum disorders. It has been well established that CHD8 has a prominent role in the development of neurons. However, there is little knowledge of its specific roles in microglia, and its possible roles in cellular functions after development, i.e. adulthood. In addition, while microglial dysfunction has been characterized in autism, the roles of autism-associated genes in microglial function have not been well characterized. Using conditional transgenic mouse models, we determined that adulthood deletion of CHD8 in microglia induces robust changes in behavior, including anxiety, social deficits, and depression-like behavior, in association with changes in microglial activation and robust microglial gene expression changes, including expression of cytokines. Of great interest, many of these changes were seen specifically in male deletion mice, and not female deletion mice. In contrast, adulthood neuron knockout had more subtle effects on behavior, mainly on depression-like behavior, and induced subtle changes in gene transcription related to the Wnt/Beta-Catenin pathway. These changes were also only present in male neuron knockout mice. In summary, CHD8 is particularly important for microglial function in adulthood and has cellular effects that are specific to males.

The Role of Alpha Synuclein in Synucleinopathy: Impact on Lipid Regulation at Mitochondria ER Membranes
The protein alpha-synuclein (Syn) plays a critical role in the pathogenesis of synucleinopathy, which includes Parkinson's disease and multiple system atrophy, and mounting evidence suggests that lipid dyshomeostasis is a critical phenotype in these neurodegenerative conditions. Previously, we identified that Syn localizes to mitochondria-associated endoplasmic reticulum membranes (MAMs), temporary functional domains containing proteins that regulate lipid metabolism, including the de novo synthesis of phosphatidylserine. In the present study, we have analyzed the lipid composition of postmortem human samples, focusing on the substantia nigra pars compacta of Parkinson's disease and controls, as well as three less affected brain regions of Parkinson's donors. To further assess synucleinopathy-related lipidome alterations, similar analyses were performed on the striatum of multiple system atrophy cases. Our data show region-and disease-specific changes in the levels of lipid species. Specifically, our data revealed alterations in the levels of specific phosphatidylserine species in brain areas most affected in Parkinson's disease. Some of these alterations, albeit to a lesser degree, are also observed multiples system atrophy. Using induced pluripotent stem cell-derived neurons, we show that Syn contributes to regulating phosphatidylserine metabolism at MAM domains, and that Syn dosage parallels the perturbation in phosphatidylserine levels. Our results support the notion that Syn pathophysiology is linked to the dysregulation of lipid homeostasis, which may contribute to the vulnerability of specific brain regions in synucleinopathy. These findings have significant therapeutic implications

Dizocilpine derivatives with neuroprotective effect lacking the psychomimetic side effects
We aimed to prepare novel dibenzosuberane derivatives that act on N-methyl-D-aspartate (NMDA) receptors with potential neuroprotective effects. Our approach involved modifying the tropane moiety of MK-801, a potent open-channel blocker known for its psychomimetic side effects, by introducing a seven-membered ring with substituted base moieties specifically to alleviate these undesirable effects. Our in silico analyses showed that these derivatives should have high gastrointestinal absorption and cross the blood-brain barrier (BBB). Our pharmacokinetic studies in rats supported this conclusion and confirmed the ability of leading compounds 3l and 6f to penetrate the BBB. Electrophysiological experiments showed that all compounds exhibited different inhibitory activity towards the two major NMDA receptor subtypes, GluN1/GluN2A and GluN1/GluN2B. Of the selected compounds intentionally differing in the inhibitory efficacy, 6f showed high relative inhibition (~90% for GluN1/GluN2A), while 3l showed moderate inhibition (~50%). An in vivo toxicity study determined that compounds 3l and 6f were safe at 10 mg/kg doses with no adverse effects. Behavioral studies demonstrated that these compounds did not induce hyperlocomotion or impair prepulse inhibition of startle response in rats. Neuroprotective assays using a model of NMDA-induced hippocampal neurodegeneration showed that compound 3l at a concentration of 30 M significantly reduced hippocampal damage in rats. These results suggest that these novel dibenzosuberane derivatives are promising candidates for developing NMDA receptor-targeted therapies with minimal psychotomimetic side effects.

Context-dependent coordination of movement in Tribolium castaneum larvae
Pest insects like Tribolium castaneum beetles cause 10.8% of global stored grain losses. However, how their nervous systems coordinate adaptive movements for successful infestation is unknown. Here, we assess how Tribolium larvae locomote over different substrates and analyze their gait kinematics across speeds. Unlike many hexapods, larvae employ a bilaterally symmetric, posterior-to-anterior wave gait during fast locomotion. During slow locomotion, thoracic intrasegmental coordination is disrupted, whilst intersegmental coordination is preserved. Additionally, terminal abdominal structures (pygopods) support challenging locomotion, such as climbing overhangs. The onset of pygopod engagement coincides with leg swing initiation, suggesting a stabilizing role. Surgically severing the connective between thoracic and abdominal ganglia impaired pygopod engagement and impeded flat-surface locomotion, climbing, and tunnelling without interrupting leg kinematics. These results suggest that thoracic-abdominal coordination underlies effective movement, and gait/limb recruitment is context-dependent. Our work provides the first kinematic analysis of Tribolium larval locomotion and insights into its neural control.

Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks.
Synaptic plasticity is a key player in the brain's life-long learning abilities. However, due to experimental limitations, the mechanistic link between synaptic plasticity rules and the network-level computations they enable remain opaque. Here we use evolutionary strategies (ES) to meta-learn local co-active plasticity rules in large recurrent spiking networks, using parameterizations of increasing complexity. We discover rules that robustly stabilize network dynamics for all four synapse types acting in isolation (E-to-E, E-to-I, I-to-E and I-to-I). More complex functions such as familiarity detection can also be included in the search constraints. However, our meta-learning strategy begins to fail for co-active rules of increasing complexity, as it is challenging to devise loss functions that effectively constrain network dynamics to plausible solutions a priori. Moreover, in line with previous work, we can find multiple degenerate solutions with identical network behaviour. As a local optimization strategy, ES provides one solution at a time and makes exploration of this degeneracy cumbersome. Regardless, we can glean the interdependecies of various plasticity parameters by considering the covariance matrix learned alongside the optimal rule with ES. Our work provides a proof of principle for the success of machine-learning-guided discovery of plasticity rules in large spiking networks, and points at the necessity of more elaborate search strategies going forward.

Steering From the Rear: Coordination of Central Pattern Generators Underlying Navigation by Ascending Interneurons
Understanding how animals coordinate movements to achieve goals is a fundamental pursuit in neuroscience. Here we explore how neurons that reside in posterior lower-order regions of a locomotor system and project to anterior higher-order regions influence steering and navigation. We characterized the anatomy and functional role of a population of ascending interneurons in the ventral nerve cord of Drosophila larvae. Through electron microscopy reconstructions and light microscopy, we determined that the cholinergic 19f cells receive input primarily from premotor interneurons and synapse upon a diverse array of postsynaptic targets within the anterior segments including other 19f cells. Calcium imaging of 19f activity in isolated CNS preparations in relation to motor neurons revealed that 19f neurons are recruited into most larval motor programmes. 19f activity lags behind motor neuron activity and as a population, the cells encode spatio-temporal patterns of locomotor activity in the larval CNS. Optogenetic manipulations of 19f cell activity in isolated CNS preparations revealed that they coordinate the activity of central pattern generators underlying exploratory headsweeps and forward locomotion in a context and location specific manner. In behaving animals, activating 19f cells suppressed exploratory headsweeps and slowed forward locomotion, while inhibition of 19f activity potentiated headsweeps, slowing forward movement. Inhibiting activity in 19f cells ultimately affected the ability of larvae to remain in the vicinity of an odor source during an olfactory navigation task. Overall, our findings provide insights into how ascending interneurons monitor motor activity and shape interactions amongst rhythm generators underlying complex navigational tasks.

Consistent neural representation of valence in watching and recall conditions
Recall is an act of elicitation of emotions similar to those emotions previously experienced. Unlike the past experiences where external sensory stimuli triggered emotions, recall does not require external sensory stimuli. This difference is pertinent to the key debate in affective representation, addressing whether the representation of valence is consistent across modalities (modality-general) or dependent on modalities (modality-specific). This study aimed to verify neural representations of valence irrespective of the presence of external sensory stimuli. Using neuroimaging data from video watching and recall (Chen et al., 2017) and behavioral data for valence ratings (Kim et al., 2020), a searchlight analysis was conducted with cross-participant regression-based decoding across the presence and absence of external stimuli. Multidimensional scaling was employed as a validation analysis of the results. The searchlight analysis revealed the right middle temporal and inferior temporal gyrus as well as the left fusiform gyrus. The validation analysis further exhibited significant consistent neural representations of valence in the inferior temporal gyrus and the left fusiform gyrus. This study identified the brain regions where valence is consistently represented, regardless of the presence of external sensory stimuli. These findings contribute to debate in affective representations, by comparing conditions utilized little in prior, suggesting the inferior temporal gyrus is related to representations of valence irrespective of the presence and absence of external visual stimuli.

Disruption of the CRF1 receptor eliminates morphine-induced sociability deficits and firing of oxytocinergic neurons in male mice
Substance-induced social behavior deficits dramatically worsen the clinical outcome of substance use disorders; yet, the underlying mechanisms remain poorly understood. Herein, we investigated the role for the corticotropin-releasing factor receptor 1 (CRF1) in the acute sociability deficits induced by morphine and the related activity of oxytocin (OXY)- and arginine-vasopressin (AVP)-expressing neurons of the paraventricular nucleus of the hypothalamus (PVN). For this purpose, we used both the CRF1 receptor-preferring antagonist compound antalarmin and the genetic mouse model of CRF1 receptor-deficiency. Antalarmin completely abolished sociability deficits induced by morphine in male, but not in female, C57BL/6J mice. Accordingly, genetic CRF1 receptor-deficiency eliminated morphine-induced sociability deficits in male mice. Ex vivo electrophysiology studies showed that antalarmin also eliminated morphine-induced firing of PVN neurons in male, but not in female, C57BL/6J mice. Likewise, genetic CRF1 receptor-deficiency reduced morphine-induced firing of PVN neurons in a CRF1 gene expression-dependent manner. The electrophysiology results consistently mirrored the behavioral results, indicating a link between morphine-induced PVN activity and sociability deficits. Interestingly, in male mice antalarmin abolished morphine-induced firing in neurons co-expressing OXY and AVP, but not in neurons expressing only AVP. In contrast, in female mice antalarmin did not affect morphine-induced firing of neurons co-expressing OXY and AVP or only OXY, indicating a selective sex-specific role for the CRF1 receptor in opiate-induced PVN OXY activity. The present findings demonstrate a major, sex-linked, role for the CRF1 receptor in sociability deficits and related brain alterations induced by morphine, suggesting new therapeutic strategy for opiate use disorders.

A bottom-up approach identifies the antipsychotic and antineoplastic trifluoperazine and the ribose derivative deoxytubercidin as novel microglial phagocytosis inhibitors.
Phagocytosis is an indispensable function of microglia, the brain professional phagocytes. Microglia are particularly efficient phagocytosing cells that undergo programmed cell death (apoptosis) in physiological conditions. However, mounting evidence suggests microglial phagocytosis dysfunction in multiple brain disorders. These observations prompted us to search for phagocytosis modulators (enhancers or inhibitors) with therapeutic potential. We used a bottom-up strategy that consisted on the identification of phagocytosis modulators using phenotypic high throughput screenings (HTSs) in cell culture and validation in organotypic cultures and in vivo. We performed two complementary HTS campagnes: at Achucarro, we used primary cultures of mouse microglia and compounds of the Prestwick Chemical Library; at Roche, we used human iPSC derived macrophage-like cells and a proprietary chemo-genomic library with 2,200 compounds with known mechanism-of-action. Next, we validated the more robust compounds using hippocampal organotypic cultures and identified two hits: trifluoperazine, a dopaminergic and adrenergic antagonist used as an antipsychotic and antineoplastic; and deoxytubercidin, a ribose derivative. Finally, we tested whether these compounds were able to modulate phagocytosis of apoptotic newborn cells in the adult hippocampal neurogenic niche in vivo by administering them into the mouse hippocampus using osmotic minipumps. We confirmed that both trifluoperazine and deoxytubercidin have anti-phagocytic activity in vivo, and validated our bottom-up strategy to identify novel phagocytosis modulators. These results show that chemical libraries with anotated mechanism of action are an starting point for the pharmacological modulation of microglia in drug discovery projects aiming at the therapeutic manipulation of phagocytosis in brain diseases.

Static and Dynamic Cross-Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients
Schizophrenia (SZ) patients exhibit abnormal static and dynamic functional connectivity across various brain domains. We present a novel approach based on static and dynamic inter-network connectivity entropy (ICE), which represents the entropy of a given network's connectivity to all the other brain networks. This novel approach enables the investigation of how connectivity strength is heterogeneously distributed across available targets in both SZ patients and healthy controls. We analyzed fMRI data from 151 schizophrenia patients and demographically matched 160 healthy controls. Our assessment encompassed both static and dynamic ICE, revealing significant differences in the heterogeneity of connectivity levels across available brain networks between SZ patients and healthy controls (HC). These networks are associated with subcortical (SC), auditory (AUD), sensorimotor (SM), visual (VIS), cognitive control (CC), default mode network (DMN) and cerebellar (CB) functional brain domains. Elevated ICE observed in individuals with SZ suggests that patients exhibit significantly higher randomness in the distribution of time-varying connectivity strength across functional regions from each source network, compared to healthy control group. C-means fuzzy clustering analysis of functional ICE correlation matrices revealed that SZ patients exhibit significantly higher occupancy weights in clusters with weak, low-scale functional entropy correlation, while the control group shows greater occupancy weights in clusters with strong, large-scale functional entropy correlation. k-means clustering analysis on time-indexed ICE vectors revealed that cluster with highest ICE have higher occupancy rates in SZ patients whereas clusters characterized by lowest ICE have larger occupancy rates for control group. Furthermore, our dynamic ICE approach revealed that it appears healthy for a brain to primarily circulate through complex, less structured connectivity patterns, with occasional transitions into more focused patterns. However, individuals with SZ seem to struggle with transiently attaining these more focused and structured connectivity patterns. Proposed ICE measure presents a novel framework for gaining deeper insights into understanding mechanisms of healthy and disease brain states and a substantial step forward in the developing advanced methods of diagnostics of mental health conditions.

Adolescent Alcohol Exposure Promotes Mechanical Allodynia and Alters Synaptic Function at Inputs from the Basolateral Amgydala to the Prelimbic Cortex
Binge drinking is common among adolescents despite mounting evidence linking it to various adverse health outcomes that includes heightened pain perception. The prelimbic (PrL) cortex is vulnerable to insults from adolescent alcohol exposure and receives input from the basolateral amygdala (BLA) while sending projections to the ventrolateral periaqueductal gray (vlPAG) - two brain regions implicated in nociception. In this study, adolescent intermittent ethanol (AIE) exposure was carried out in male and female rats using a vapor inhalation procedure. Mechanical and thermal sensitivity, assessed throughout adolescence and into adulthood, revealed that AIE exposure induced protracted mechanical allodynia in both male and female rats. However, a carrageenan inflammatory paw pain challenge in adult rats revealed that AIE did not further augment carrageenan-induced hyperalgesia. To investigate synaptic function at BLA inputs onto defined populations of PrL neurons, retrobeads and viral labelling were combined with optogenetics and slice electrophysiology. Recordings from retrobead labelled cells in the PrL revealed AIE reduced BLA driven feedforward inhibition of neurons projecting from the PrL to the vlPAG (PrLPAG neurons), resulting in augmented excitation/inhibition (E/I) balance and increased intrinsic excitability. Consistent with this finding, recordings from virally tagged PrL parvalbumin interneurons (PVINs) demonstrated that AIE exposure reduced both E/I balance at BLA inputs onto PVINs and PVIN intrinsic excitability when assessed in adulthood. These findings provide compelling evidence that AIE and acute pain alter synaptic function and intrinsic excitability within a prefrontal nociceptive circuit.

The UPRER governs the cell-specific response of human dopaminergic neurons to mitochondrial stress
Mitochondrial dysfunction is thought to be central to the pathophysiology of Parkinson's disease. The preferential vulnerability of dopaminergic (DA) neurons of the substantia nigra pars compacta to mitochondrial stress may underlie their massive degeneration and the occurrence of motor symptoms. Using LUHMES-derived DA neurons, we demonstrated that inhibition of the mitochondrial electron transport chain resulted in a severe alteration of mitochondrial turnover, pushing the balance towards mitochondrial loss, a reduction of the maturation status of the DA population and an increased proportion of apoptotic cells. PERK-mediated Unfolded Protein Response of the Endoplasmic Reticulum (UPRER) emerged as the key coordinator of the stress response, governing the inactivation of the mitochondrial UPR (UPRmt), the initiation of mitophagy and the cell-specific expression of long non-coding RNAs (lncRNAs). Importantly, we discovered novel lncRNAs specifically expressed in human DA neurons upon stress. Among them, we showed that lnc-SLC6A15-5 contributes to the resumption of translation after mitochondrial stress.

Posterior parietal cortex maps progress along routes sharing the same meta-structure
Neurons of posterior parietal cortex were recorded as rats performed a working memory task within a network of intersecting paths. The specific routes utilized in task performance provided opportunity to contrast responses of posterior parietal cortex sub-populations to linear and angular velocity with more complex responses that map route progress. We found evidence for the presence of posterior parietal cortex neurons that generalize in their firing patterns across routes having the same shape but opposite action series. The results indicate that posterior parietal cortex has the capacity to generalize the mapping of route progress independent of the specific actions taken to move through those routes. We suggest that such encoding can form the basis for learning the meta-structural organization of a non-random path network structure, such as that commonly found in cities.

The spatial layout of antagonistic brain regions are explicable based on geometric principles
Brain activity emerges in a dynamic landscape of regional increases and decreases that span the cortex. Increases in activity during a cognitive task are often assumed to reflect the processing of task-relevant information, while reductions can be interpreted as suppression of irrelevant activity to facilitate task goals. Here, we explore the relationship between task-induced increases and decreases in activity from a geometric perspective. Using a technique known as kriging, developed in earth sciences, we examined whether the spatial organisation of brain regions showing positive activity could be predicted based on the spatial layout of regions showing activity decreases (and vice versa). Consistent with this hypothesis we established the spatial distribution of regions showing reductions in activity could predict (i) regions showing task-relevant increases in activity in both groups of humans and single individuals; (ii) patterns of neural activity captured by calcium imaging in mice; and, (iii) showed a high degree of generalisability across task contexts. Our analysis, therefore, establishes that antagonistic relationships between brain regions are topographically determined, a spatial analog for the well documented anti-correlation between brain systems over time.

Differential Effects of Haloperidol on Neural Oscillations During Wakefulness and Sleep
The electrical activity of the brain, characterized by its frequency components, reflects a complex interplay between periodic (oscillatory) and aperiodic components. These components are associated with various neurophysiological processes, such as the excitation-inhibition balance (aperiodic activity) or interregional communication (oscillatory activity). However, we do not fully understand whether these components are truly independent or if different neuromodulators modulate them in different ways. The dopaminergic system has a critical role for cognition and motivation, being a potential modulator of these power spectrum components. To improve our understanding of these questions, we investigated the differential effects of this system on these components using electrocorticogram recordings in cats, which show clear oscillations and aperiodic 1/f activity. Specifically, we focused on the effects of haloperidol (a D2 receptor antagonist) on oscillatory and aperiodic dynamics during wakefulness and sleep. By parameterizing the power spectrum into these two components, our findings reveal a state-dependent modulation of oscillatory activity by the D2 receptor across the brain. Surprisingly, aperiodic activity was not significantly affected and exhibited inconsistent changes across the brain. This suggests a nuanced interplay between neuromodulation and the distinct components of brain oscillations, providing insights into the selective regulation of oscillatory dynamics in awake states.

Synchronicity transitions determine connection fluctuations in a model of coupled oscillators with plasticity
Sleep and rest are crucial for knowledge reorganization and creativity. During these periods, synapses between neurons are plastically altered and neuronal activities are collectively synchronized, accompanied by large differences in excitation-inhibition (EI) balance. These processes are assumed to be dissimilar from the learning process during task engagement. The detailed mechanism of how synchronized neuronal activities modify neural circuits via plasticity has yet to be fully understood. The Kuramoto model is utilized to study the collective synchronization of oscillators, including neurons. We previously proposed the EI-Kuramoto model, in which the EI balance was implemented in the Kuramoto model. The model alters its synchronicity based on the EI balance of the interaction strength. In this study, we developed this EI-Kuramoto model by implementing plasticity, leading to the plastic EI-Kuramoto (pEI-Kuramoto) model. Models with high inhibition displayed desynchronized dynamics and consistent connection strengths. Models with low inhibition exhibited bistable dynamics between synchronized and desynchronized states and fluctuation of interaction strengths in middle strength connections, while the strongest connections remained stable. These results, stabilizing a few strong connections and fluctuating the other connections in low inhibition conditions, could facilitate knowledge abstraction and reorganization. Our findings shed light on how varying inhibitory effects influence network stability and coupling, offering deeper insights into synaptic networks and knowledge reshaping.

Cardiometabolic health, cortical thickness, and neurotransmitter systems: a large-scale multivariate study
There is a recognized link between risk factors for non-communicable diseases and brain health. However, the specific effects that they have on brain health are still poorly understood, preventing its implementation in clinical practice. For instance, the association between such risk factors and cortical thickness (CT) has been primarily explored using univariate/bivariate methods and global/lobar measures of CT and has yielded inconsistent results. In this work, we aim to study the relationship between risk factors for non-communicable diseases and CT. In addition, we adopt a systems-level perspective to understand such relationship, by integrating several brain features including brain structure and function as well as neurotransmitter systems.

Here, we analyzed latent dimensions linking a broad set of risk factors for non-communicable diseases to parcel-wise CT across the whole cortex (including raw, proportional, and brain size- corrected measures). We used a multivariate approach (regularized canonical correlation analysis (RCCA)) embedded in a machine learning framework that allows to capture inter- individual variability and to assess the generalizability of the model. The brain patterns (captured in association with risk factors) were characterized from a multi-level perspective, by comparing them with patterns of brain structure, function, and neurotransmitter systems. Analyses were performed separately in women (n=3685, 46-81 years) and in age-matched men (n=3685, 46-81 years) to avoid sex-bias on the results.

We found one significant latent dimension (women: rrange=0.25-0.30, p=0.005-0.005; men: rrange=0.31-0.34, p=0.005-0.005), capturing variability in cardiometabolic health, including physical activity, body morphology/composition, basal metabolic rate, and blood pressure. This cardiometabolic health dimension was linked to a CT axis of inter-individual variability from the insula and cingulate cortex to occipital and parietal areas. Interestingly, this brain pattern was associated with the binding potentials of several neurotransmitter systems, including serotoninergic, dopaminergic, cholinergic, and GABAergic systems. Of note, this latent dimension was similar across sexes and across CT measures (raw, proportional, and brain-size corrected).

We observed a robust, multi-level and multivariate link between cardiometabolic health, CT, and neurotransmitter systems. These findings support the urgency of further investigation into the interaction between brain health and physical health and contributes to the challenge to the classical conceptualization of neuropsychiatric and physical illnesses as categorical entities. Therefore, regular monitoring of cardiometabolic risk factors may reduce their adverse effects on brain health and prevent the development of brain diseases.

Event structure sculpts neural population dynamics in the lateral entorhinal cortex
Our experience of the world is a continuous stream of events which must be segmented and organized simultaneously at multiple timescales. The neural mechanisms underlying this process remain unknown. Here, we simultaneously recorded many hundreds of neurons in the lateral entorhinal cortex (LEC) of freely behaving rats as we manipulated event structure at multiple timescales. During foraging as well as during sleep, population activity drifted continuously and unidirectionally along a one-dimensional manifold. Boundaries between events were associated with discrete shifts in state space, suggesting that LEC dynamics directly reflect event segmentation. During tasks with a recurring temporal structure, activity traveled additionally in directions orthogonal to the flow of drift, enabling the LEC population to multiplex event information across different timescales. Taken together, these results identify a hierarchically organized neural coding scheme for segmenting and organizing events in time.

Rapid rebalancing of co-tuned ensemble activity in the auditory cortex
Sensory information is represented by small neuronal ensembles in sensory cortices. Neuronal activity shows high trial-by-trial variability in that repeated presentation of the same stimulus, e. g., multiple presentations of the same sound activate differing ensembles in the auditory cortex (AC). How the differing ensembles interact to selectively activate to process incoming sound inputs with reduced energy is unknown. Efficient processing of complex acoustic signals requires that these sparsely distributed neuronal ensembles actively interact in order to provide a constant percept. Here, we probe interactions within and across ensembles by combining in vivo 2-photon Ca2+ imaging and holographic optogenetic stimulation to study how increased activity of single cells level affects the cortical network. We stimulated a small number of neurons sharing the same frequency preference alongside the presentation of a target pure tone, further increasing their tone-evoked activity. We found that other non-stimulated co-tuned neurons decreased their tone-evoked activity while non co-tuned neurons were unaffected. This shows that co-tuned ensembles communicated and balanced their total activity across the network. The rebalanced activity due to external stimulation remained constant. These effects suggest that co-tuned ensembles in AC interact and rapidly rebalance their activity to maintain encoding homeostasis, and that the rebalanced network is persistent.

Social threat alters the behavioral structure of social motivation and reshapes functional brain connectivity
Traumatic social experiences redefine socially motivated behaviors to enhance safety and survival. Although many brain regions have been implicated in signaling a social threat, the mechanisms by which global neural networks regulate such motivated behaviors remain unclear. To address this issue, we first combined traditional and modern behavioral tracking techniques in mice to assess both approach and avoidance, as well as sub-second behavioral changes, during a social threat learning task. We were able to identify previously undescribed body and tail movements during social threat learning and recognition that demonstrate unique alterations into the behavioral structure of social motivation. We then utilized inter-regional correlation analysis of brain activity after a mouse recognizes a social threat to explore functional communication amongst brain regions implicated in social motivation. Broad brain activity changes were observed within the nucleus accumbens, the paraventricular thalamus, the ventromedial hypothalamus, and the nucleus of reuniens. Inter-regional correlation analysis revealed a reshaping of the functional connectivity across the brain when mice recognize a social threat. Altogether, these findings suggest that reshaping of functional brain connectivity may be necessary to alter the behavioral structure of social motivation when a social threat is encountered.

Age-dependent H3K9 trimethylation by dSetdb1 impairs mitochondrial UPR leading to degeneration of olfactory neurons and loss of olfactory function in Drosophila.
Aging is characterized by a decline in essential sensory functions, including olfaction, which is crucial for environmental interaction and survival. This decline is often paralleled by the cellular accumulation of dysfunctional mitochondria, particularly detrimental in post-mitotic cells such as neurons. Mitochondrial stress triggers the mitochondrial unfolded protein response (UPRMT), a pathway that activates mitochondrial chaperones and antioxidant enzymes. Critical to the efficacy of the UPRMT is the cellular chromatin state, influenced by the methylation of lysine 9 on histone 3 (H3K9). While it has been observed that the UPRMT response can diminish with an increase in H3K9 methylation, its direct impact on age-related neurodegenerative processes, especially in the context of olfactory function, has not been clearly established. Using Drosophila, we demonstrate that an age-dependent increase in H3K9 trimethylation by the methyltransferase dSetdb1 reduces the activation capacity of the UPRMT in olfactory projection neurons leading to neurodegeneration and loss of olfactory function. Age-related neuronal degeneration was associated with morphological alterations in mitochondria and an increase in reactive oxygen species levels. Importantly, forced demethylation of H3K9 through knockdown of dSetdb1 in olfactory projection neurons restored the UPRMT activation capacity in aged flies, and suppressed age-related mitochondrial morphological abnormalities. This in turn prevented age-associated neuronal degeneration and rescued age-dependent loss of olfactory function. Our findings highlight the effect of age-related epigenetic changes on the response capacity of the UPRMT, impacting neuronal integrity and function. Moreover, they suggest a potential therapeutic role for UPRMT regulators in age-related neurodegeneration and loss of olfactory function.

Reelin marks cocaine-activated striatal ensembles, promotes neuronal excitability, and regulates cocaine reward
Drugs of abuse activate defined neuronal ensembles in brain reward structures such as the nucleus accumbens (NAc), which are thought to promote the enduring synaptic, circuit, and behavioral consequences of drug exposure. While the molecular and cellular effects arising from experience with drugs like cocaine are increasingly well understood, the mechanisms that sculpt NAc ensemble participation are largely unknown. Here, we leveraged unbiased single-nucleus transcriptional profiling to identify expression of the secreted glycoprotein Reelin (encoded by the Reln gene) as a marker of cocaine-activated neuronal ensembles within the rat NAc. Multiplexed in situ detection confirmed selective expression of the immediate early gene Fos in Reln+ neurons after cocaine experience, and also revealed enrichment of Reln mRNA in Drd1+ medium spiny neurons (MSNs) in both the rat and human brain. Using a novel CRISPR interference strategy enabling selective Reln knockdown in the adult NAc, we observed altered expression of genes linked to calcium signaling, emergence of a transcriptional trajectory consistent with loss of cocaine sensitivity, and a striking decrease in MSN intrinsic excitability. At the behavioral level, loss of Reln prevented cocaine locomotor sensitization, abolished cocaine place preference memory, and decreased cocaine self-administration behavior. Together, these results identify Reelin as a critical mechanistic link between ensemble participation and cocaine-induced behavioral adaptations.