bioRxiv Subject Collection: Neuroscience's Journal

Absolute measurement of fast and slow neuronal signals with fluorescence lifetime photometry at high temporal resolution
The concentrations of extracellular and intracellular signaling molecules, such as dopamine and cAMP, change over both fast and slow timescales and impact downstream pathways in a cell-type specific manner. Fluorescence sensors currently used to monitor such signals in vivo are typically optimized to detect fast, relative changes in concentration of the target molecule. They are less well suited to detect slowly-changing signals and rarely provide absolute measurements of either fast and slow signaling components. Here, we developed a system for fluorescence lifetime photometry at high temporal resolution (FLIPR) that utilizes frequency-domain analog processing to measure the absolute fluorescence lifetime of genetically-encoded sensors at high speed but with long-term stability and picosecond precision in freely moving mice. We applied FLIPR to investigate dopamine signaling in two functionally distinct regions in the striatum, the nucleus accumbens core (NAC) and the tail of striatum (TOS). We observed higher tonic dopamine levels at baseline in the TOS compared to the NAC and detected differential and dynamic responses in phasic and tonic dopamine to appetitive and aversive stimuli. Thus, FLIPR enables simple monitoring of fast and slow time-scale neuronal signaling in absolute units, revealing previously unappreciated spatial and temporal variation even in well-studied signaling systems.

Memory engram synapse 3D molecular architecture visualized by cryoCLEM-guided cryoET
Memory is incorporated into the brain as physicochemical changes to engram cells. These are neuronal populations that form complex neuroanatomical circuits, are modified by experiences to store information, and allow for memory recall. At the molecular level, learning modifies synaptic communication to rewire engram circuits, a mechanism known as synaptic plasticity. However, despite its functional role on memory formation, the 3D molecular architecture of synapses within engram circuits is unknown. Here, we demonstrate the use of engram labelling technology and cryogenic correlated light and electron microscopy (cryoCLEM)-guided cryogenic electron tomography (cryoET) to visualize the in-tissue 3D molecular architecture of engram synapses of a contextual fear memory within the CA1 region of the mouse hippocampus. Engram cells exhibited structural diversity of macromolecular constituents and organelles in both pre- and postsynaptic compartments and within the synaptic cleft, including in clusters of membrane proteins, synaptic vesicle occupancy, and F-actin copy number. This "engram to tomogram" approach, harnessing in vivo functional neuroscience and structural biology, provides a methodological framework for testing fundamental molecular plasticity mechanisms within engram circuits during memory encoding, storage and recall.

Sleep increases propagation speed of physiological brain pulsations
During sleep, there is an increase in the brain cerebrospinal fluid (CSF) solute convection driven by physiological pulsations. Although the main drivers of CSF flow, namely cardiac, respiratory, and vasomotor pulsations, become more powerful during sleep, there is relatively little information regarding their effects on CSF flow velocity across human brain during sleep. Here, we used functional magnetic resonance encephalography (MREG) to measure non-invasively changes in brain water flow during to sleep by tracking the propagating ultrafast signal changes induced by physiological brain pulsations. We first undertook a phantom study confirming that dense optical flow analysis of MREG data accurately detects water flow velocity, and reflects the power of the physiological pulsations. We then applied the method to quantify CSF water flow velocity in brain of healthy volunteers during EEG-verified awake and sleep recordings of ultrafast MREG data. Sleep induced an increase in CSF flow speed, as demonstrated by elevated vasomotor and respiratory pulsation speeds, while the speed of cardiovascular impulse propagation remained unchanged. The speed increases match previous findings of respective pulsation power changes, and correlated with slow delta EEG power. The sleep-induced CSF flow speed increases occurred dynamically over both pulsation cycles, without the large effects on flow directions reported previously in several neurological conditions. In conclusion, sleep increases 3D water flow speed dynamically in human brain regions showing concomitant pulse power increases, supporting a porous media model of hydrodynamics in brain cortex.

Constructing structural and functional brain networks from regional brain profiles
Brain network analysis has become an important approach to understanding brain function. Given the human brain's complexity and dynamic nature, traditional brain networks based on temporal synchronization may not capture all the nuances of brain activity. The emerging trend is to construct brain networks from regional information, creating pathways that connect regional profiles to network-level insights to better understand brain function. In this study, we constructed structural networks based on regional brain structural information, specifically gray matter volume (GMV), and functional networks based on regional brain activity, measured by brain entropy (BEN). We compared these newly constructed networks with traditional networks: functional connectivity networks (FCN) based on temporal synchronization, structural connectivity networks (SCN) derived from fiber tracking, and MEG-derived functional networks. Our results reveal that GMV network (GMVN) and BEN network (BENN) show correlations with these networks but also exhibit distinct differences. Furthermore, we conducted connectome gradient analyses, uncovering meaningful brain function distribution patterns in both GMVN and BENN. Finally, we used GMVN, BENN, and traditional FCN to predict cognitive and emotional scores. The results showed that BENN, in the resting state, provided the best prediction of both cognitive and emotional scores. This study systematically evaluates the relationship between brain networks constructed from regional brain information and existing networks, as well as their ability to predict behavioral phenotypes. It demonstrates that networks built from regional information capture aspects of brain activity that traditional networks cannot represent and may even provide superior predictive power for behavioral phenotypes. This opens a new path for understanding brain function from regional to network-level information and lays the foundation for future applications in brain development, individual differences, and clinical research.

Autosuggestion and Mental Imagery Bias the Perception of Social Emotions
Cognitive processes that modulate social emotion perception are of pivotal interest for psychological and clinical research. Autosuggestion and mental imagery are two candidate processes for such a modulation, however, their precise effect on social emotion perception has not yet been clarified. Here, we investigated if autosuggestion and mental imagery during an adaptation period influence the perception of subsequent facial emotions, and if so, to which extent. Separate cohorts of participants took part in five experiments, where they either mentally affirmed (autosuggested, Experiments 1a and 1b) or imagined (Experiment 2) that a neutral face would be expressing a specific emotion (happy or sad). Subsequent facial emotion perception was then assessed by calculating points of subjective equality (PSEs) along a happiness-sadness continuum. Our results show that both autosuggestion and mental imagery induce a bias toward perceiving facial emotions in the direction of the desired emotion, with larger Bayes factors supporting autosuggestion. Experiment 3 confirmed no effects when emotional words were presented instead, suggesting a reduced role of response bias to drive this effect. Finally, experiment 4 validated the experimental setup by demonstrating standard contrastive aftereffects when participants are adapted to actual, physical emotional faces. Together, our findings provide an initial step toward understanding the potential of intentional cognitive processes to modulate social emotions, specifically by biasing emotional face perception. With comparable effect sizes observed for both autosuggestion and mental imagery, these strategies appear promising as tools for self-directed interventions.

Overcoming pride via the dorsal ACC underlies acceptance of unfair offers
Bargaining is a fundamental social behavior in which individuals often accept unfair offers. Traditional behavioral models, based solely on choice data, typically interpret this acceptance as simple reward-maximization. However, the suppression of emotions such as inequity aversion or pride may also play a critical role in this decision. Incorporating response time alongside choice data provides a means to quantify participants' internal conflict in suppressing these emotions and deciding to accept unfair offers. In this study, we conducted functional magnetic resonance imaging (fMRI) of the ultimatum game, where participants decided within 10 seconds whether to accept or reject monetary distribution offers from a proposer. Using the drift diffusion model (DDM), we quantified decision-making dynamics based on both choice and response time. Participants who suppressed disadvantageous inequity (DI)-driven rejection (reflected by a lower DDM weight for DI) exhibited heightened dorsal anterior cingulate cortex (dACC) activity in response to DI. Functional connectivity analysis revealed a negative correlation between the dACC and the ventrolateral prefrontal cortex (vlPFC) when DI was large, which encoded both the rejection rates, and the response times associated with accepting DI offers. Furthermore, vlPFC activity was significantly correlated with amygdala activity during high DI conditions, specifically encoding response time for accepting DI offers but not rejection rates. Importantly, these findings could not be captured using standard value-based models that rely solely on choice data. Our results underscore the dACC's critical role in mediating the suppression of emotional responses to DI, enabling the acceptance of unfair offers in a dynamic bargaining process.

Alprazolam induces anterograde amnesia for contextual fear memory and alters dorsoventral hippocampal neuronal ensembles in female mice
Benzodiazepines (BZDs) are commonly prescribed anxiolytic drugs that act on GABAa receptors, and can result in anterograde amnesia, or the inability to form new memories. While BZDs have been used for decades, the brain regions and neuronal mechanisms responsible for this detrimental side effect are largely unknown at the systems neuroscience level. To analyze the effects of BZDs on long-term memory, activity-dependent ArcCreERT2 x eYFP mice were injected with Alprazolam 30 minutes prior to a 3-shock contextual fear conditioning (CFC) procedure and encoding ensembles were tagged with eYFP. Mice were re-exposed to the same context 5 days later, and retrieval cell activation was analyzed using the immediate early gene (IEG), c-Fos, allowing us to determine which brain regions undergo changes after alprazolam injection. Additionally, we address the question of whether alprazolam induces state-dependent memory by altering the timelines of injection. We found that 1) alprazolam treated male and female mice exhibit a decrease in memory retention and, 2) alprazolam treated female and male mice show a decrease in memory retention with saline injection prior to re-exposure, 3) alprazolam treated female mice exhibit increased EYFP+ (encoding) activation in the dCA1 and enhanced engram activation in the dCA3, and 4) alprazolam treated females showed less c-Fos+ activation in the vCA1. These results suggest that alprazolam induces sex-specific ensemble activation throughout the hippocampus and will help us understand the long-term memory deficits associated with BZD use.

PHYSICAL EXERCISE RESTORES NEUROCOGNITIVE HOMEOSTASIS DISRUPTED BY NON-SEVERE MURINE MALARIA
Malaria disrupts neurocognitive homeostasis in humans, including in the non-severe manifestation of the disease - which is the most prevalent form of malaria in the world. This disruption is classically observed in human and experimental models of cerebral malaria. More recently, we demonstrated that this can also be observed in an experimental model of non-severe malaria and that Th2-immune response improves cognition and attenuates anxiety-like behavior associated to malaria. Complementarily, we have been studying the effect of physical exercise in restoring the neurocognitive homeostasis lost after non-severe murine malaria.

ACTIVITY IN HUMAN DORSAL RAPHE NUCLEUS SIGNALS CHANGES IN BEHAVIOURAL POLICY
The dorsal raphe nucleus (DRN) is an important source of serotonin to the human forebrain, however there is little consensus about its behavioural function. We build on recent results from animal models to demonstrate that activity in human DRN represents changes between general behavioural policies. We use a novel behavioural task to show that human participants change their policy to pursue or reject reward opportunities as a function of the average value of opportunities in the environment. Activity in DRN - but no other neuromodulatory nucleus - signalled such policy changes. Patterns of multivariate activity in dorsal anterior cingulate cortex (dACC) and anterior insular cortex (AI), meanwhile, tracked the relative value of reward opportunities given the average value of the environment. We therefore suggest that DRN, dACC and AI form a circuit in which dACC/AI compute the relative value of reward opportunities given the current context, and DRN implements changes in behavioural policy based on context-specific values.

A Mean Field Theory for Pulse-Coupled Oscillators based on the Spike Time Response Curve
A mean field method for pulse-coupled oscillators with delays used a self-connected oscillator to represent a synchronous cluster of N-1 oscillators and a single oscillator assumed to be perturbed from the cluster. A periodic train of biexponential conductance input was divided into a tonic and a phasic component representing the mean field input. A single cycle of the phasic conductance from the cluster was applied to the single oscillator embedded in the tonic component at different phases to measure the change in the cycle length which the perturbation was initiated, that is, the first order phase response curve (PRC), and the second order PRC in the following cycle. A homogeneous network of 100 biophysically calibrated inhibitory interneurons with either shunting or hyperpolarizing inhibition tested the predictive power of the method. A self-consistency criterion predicted the oscillation frequency of the network from the PRCs as a function of the synaptic delay. The major determinant of the stability of synchrony was the sign of the slope of the first order PRC of the single oscillator in response to an input from the self-connected cluster at a phase corresponding to the delay value. For most short delays, first order PRCs correctly predicted the frequency and stability of simulated network activity. However, considering the second order PRC improved the frequency prediction and resolved an incorrect prediction of stability of global synchrony at delays close to the free running period of single neurons in which a discontinuity in the PRC precluded existence of 1:1 self-locking.

Regenerative failure of sympathetic axons contributes to deficits in functional recovery after nerve injury
Renewed scientific interest in sympathetic modulation of muscle and neuromuscular junctions has spurred a flurry of new discoveries with major implications for motor diseases. However, the role sympathetic axons play in the persistent dysfunction that occurs after nerve injuries remains to be explored. Peripheral nerve injuries are common and lead to motor, sensory, and autonomic deficits that result in lifelong disabilities. Given the importance of sympathetic signaling in muscle metabolic health and maintaining bodily homeostasis, it is imperative to understand the regenerative capacity of sympathetic axons after injury. Therefore, we tested sympathetic axon regeneration and functional reinnervation of skin and muscle, both acute and long-term, using a battery of anatomical, pharmacological, chemogenetic, cell culture, analytical chemistry, and electrophysiological techniques. We employed several established growth-enhancing interventions, including electrical stimulation and conditioning lesion, as well as an innovative tool called bioluminescent optogenetics. Our results indicate that sympathetic regeneration is not enhanced by any of these treatments and may even be detrimental to sympathetic regeneration. Despite the complete return of motor reinnervation after sciatic nerve injury, gastrocnemius muscle atrophy and deficits in muscle cellular energy charge, as measured by relative ATP, ADP, and AMP concentrations, persisted long after injury, even with electrical stimulation. We suggest that these long-term deficits in muscle energy charge and atrophy are related to the deficiency in sympathetic axon regeneration. New studies are needed to better understand the mechanisms underlying sympathetic regeneration to develop therapeutics that can enhance the regeneration of all axon types.

Vascular contribution to cognitive impairment in heart failure with preserved ejection fraction: TRPV4 and KLF2 as key mediators of neurovascular dysfunction in the ZSF1 model
Background The development of vascular cognitive impairment (VCI) and heart failure with preserved ejection fraction (HFpEF) are strongly associated with comorbidities such as obesity, diabetes, hypertension, and aging. Microvascular dysfunction may be key a pathological step in the development of cognitive dysfunction during HFpEF. Hence, we aimed to evaluate the cerebrovascular and cognitive phenotype in ZSF1 rats and identify molecular processes central to the development of VCI during HFpEF. Methods Male Lean and Obese rats underwent blood pressure and glucose measurements, echocardiography and a series of behavioural tasks at three different time points. Cerebral blood flow was measured over the barrel cortex using laser speckle contrast imaging and neurovascular coupling was assessed upon whisker stimulation. Brain immunohistochemistry was performed to assess blood-brain barrier (BBB) integrity and vascular density. Lastly, isolated cortical microvessels were used for transcriptomic analysis, and selected targets were validated in brain sections via fluorescent multiplex in-situ hybridization. Results Obese ZSF1 rats exhibited neurovascular uncoupling, along with an impaired short- and long-term memory, as well as spatial learning. In addition, BBB permeability and cerebral vascular density were elevated in Obese vs Lean at 22-23 and 34-35 weeks of age, respectively. Transcriptomic analysis of brain microvessels revealed the regulation of processes related to angiogenesis, vasoreactivity, immune mechanisms and vascular remodelling. Among the top regulated biological processes, Trpv4 and Klf2 were found to be consistently downregulated in Obese vs Lean rats and involved in many of the top regulated biological processes. This was further verified in brain sections at 22-23 weeks of age. Conclusion Obese ZSF1 rats develop cognitive impairment, which is related to dysfunction of the neurovascular unit. This cerebrovascular phenotype progresses along with the onset of HFpEF and is associated with downregulation of Trpv4 and Klf2 in cerebral microvessels, two key genes known for their vasoprotective actions.

Monte Carlo simulations predict distinct real EEG patterns in individuals with high and low IQs
The neural mechanisms underlying individual differences in intelligence are a central focus in neuroscience. We investigated the effectiveness of Monte Carlo simulations in predicting real EEG patterns and uncovering potential neural differences between individuals with high and low intelligence. EEG data were collected from two groups of volunteers categorized by IQ, namely, a high-IQ group and a low-IQ group. A univariate normal distribution was fitted to each EEG channel using Maximum Likelihood Estimation, after which synthetic datasets were generated based on the estimated parameters. Statistical analyses including Root Mean Square Error (RMSE) calculations assessed the alignment between real and simulated data. We showed that Monte Carlo simulations effectively replicated the statistical properties of the EEG data from both the groups, closely matching the real central tendencies, variability and overall distribution shapes. Specific EEG channels, particularly in the frontal and temporal bilateral regions, exhibited significant differences between the two groups, pointing to potential neural markers of cognitive abilities. Further, the low-IQ group exhibited higher predictability and more consistent neural patterns, reflected by lower RMSE values and smaller standard deviations across several EEG channels. Conversely, the high-IQ group displayed greater variability and larger RMSE values, reflecting complex neural dynamics that are less predictable by Monte Carlo simulations. Our findings underscore the utility of Monte Carlo simulations as a robust tool for replicating EEG patterns, identifying cognitive differences and predicting EEG activity associated with intelligence levels. These insights can inform predictive modeling, neurocognitive research, educational strategies and clinical interventions of targeted cognitive enhancement.

Machine learning identifies routine blood tests as accurate predictive measures of pollution-dependent poor cognitive function
Background: Several modifiable risk factors for dementia and related neurodegenerative diseases have been identified including education level, socio-economic status, and environmental exposures; however, how these population-level risks relate to individual risk remains elusive. To address this, we assess over 450 potential risk factors in one deeply clinically and demographically phenotyped cohort using random forest classifiers to determine predictive markers of poor cognitive function. This study aims to understand early risk factors for dementia by identifying predictors of poor cognitive performance amongst a comprehensive battery of imaging, blood, atmospheric pollutant and socio-economic measures. Methods: Random forest modelling was used to determine significant predictors of poor cognitive performance in a cohort of 324 individuals (age 61.6 +/- 4.8 years; 150 males, 174 females) without extant neurological disease. 457 features were assessed including brain imaging measures of volume and iron deposition, blood measures of anaemia, inflammation, and heavy metal levels, social deprivation indicators and atmospheric pollution exposure. Results: Routinely assessed markers of anaemia including mean corpuscular haemoglobin concentration were identified as robust predictors of poor general cognition, where both extremes (low and high) were associated with poor cognitive performance. The strongest, most consistent predictors of poor cognitive performance were environmental measures of atmospheric pollution, in particular, lead, carbon monoxide, and particulate matter. Feature analysis demonstrated a significant negative relationship between low mean corpuscular haemoglobin concentration and high levels of atmospheric pollutants highlighting the potential of routinely assessed blood tests as a predictive measure of pollution-dependent cognitive functioning, at an individual level. Conclusions: Taken together, these data demonstrate how routine, inexpensive medical testing and local authority initiatives could help to identify and protect at-risk individuals. These findings highlight the potential to identify individuals for targeted, cost effective medical and social interventions to improve population cognitive health.

Kynurenine Metabolism is Associated with Antidepressant Response to Selective Serotonin Reuptake Inhibitors
Alterations in the kynurenine pathway, and in particular the balance of neuroprotective and neurotoxic metabolites, have been implicated in the pathophysiology of Major Depressive Disorder (MDD) and antidepressant treatment response. In this study, we examined the relationship between changes in kynurenine pathway activity (Kynurenine/Tryptophan ratio), focusing on the balance of neuroprotective-to neurotoxic metabolites (Kynurenic Acid/Quinolinic Acid and Kynurenic Acid/3-Hydroxykynurenine ratios), and response to 8 weeks of selective serotonin reuptake inhibitor (SSRI) treatment, including early changes four weeks after SSRI initiation. Additionally, we examined relationships between kynurenine metabolite ratios and three promising biomarkers of depression and antidepressant response: amygdala/hippocampal volume, and glutamate metabolites in the anterior cingulate cortex. Responders showed an increase in the Kynurenic Acid/3-Hydroxykynurenine ratio by week 8 (F(1,46) = 11.92, p = .001) and early increases in the Kynurenine/Tryptophan ratios at week 4 (F(2,58) = 5.224, p = .008), while Non-Responders did not. Pre-treatment Kynurenic Acid/Quinolinic Acid and Kynurenic Acid/3-Hydroxykynurenine ratios were positively associated with right amygdala volume ({beta} = . 247 p = .032 and {beta} = .245 p = .028, respectively). Lastly, in a subset of participants, pre-treatment Kynurenic Acid/3-Hydroxykynurenine ratio showed a positive, small effect size association with glutamate metabolites (Glx) in the anterior cingulate cortex ({beta} = .307 p = .079), which became significant post-treatment with a large effect size ({beta} = .652 p = .021). These results suggest that response to SSRIs may arise from shifting the balance from neurotoxic to neuroprotective kynurenine metabolites.

Longitudinal Stability of Mood-Related Resting-State Networks in Youth with Symptomatic Bipolar-I/II Disorder
Bipolar disorder (BD) is characterized by temporal instability of mood and energy, but the neural correlates of this instability are poorly understood. In previous cross-sectional studies, mood state in BD has been associated with differential functional connectivity (FC) amongst several subcortical regions and ventromedial prefrontal cortex. Here, we assess whether BD is associated with longitudinal instability within this mood-related network of interest (NOI). Young people with BD-I/II were scanned 4-6 times and healthy controls (HC) were scanned 4 times over 9 months. Following preprocessing of 20-minute resting-state scans, we assessed across-scan correlation of FC, focusing on FC between regions previously associated with BD mood state. Utilizing Bayesian models, we assessed the relationship between diagnostic group and within-person, across-scan correlation, adjusting for motion, time-of-day, and inter-scan interval; prediction intervals (PI) are reported. In a sample of 16 youth (11 BD, 5 HC; 16.3-23.3 years old) with 70 scans (50 BD, 20 HC), across-scan NOI stability was higher within- than between-person (0.70 vs. 0.54; p<.0001). BD (vs. HC) within-person scan-pairs showed lower NOI stability (mean -0.109; 95% PI -0.181, -0.038), distinguishing BD vs. HC with excellent accuracy (AUC=0.95). NOI instability was more pronounced with manic symptoms (mean -0.012; 95% PI -0.023, -0.0002) and in BD-II (vs. BD-I; mean -0.071; 90% PI -0.136, -0.007). Results persisted after accounting for medications, comorbidity, and sleep/arousal measures. Within this pilot sample, BD is characterized by less within-person stability of a mood-related NOI. While preliminary, these results highlight a possible role for precision imaging approaches to elucidate neural mechanisms underlying BD.

Loss of Effort in Chronic Low-Back Pain Patients: Motivational Anhedonia in Chronic Pain
The motivational and affective properties of chronic pain significantly impact patients lives and response to treatment but remain poorly understood. Most available phenotyping tools of chronic pain affect rely on patients self-report. Here we instead directly studied the willingness of chronic low-back pain (CLBP) patients to expend effort to win monetary rewards available for wins at different probabilities and different levels of difficulties in comparison to matched pain free controls and obtained functional brain imaging on a sub-group of our sample to link behavior to brain properties. We aimed to specifically test for a differential relationship of the functional connectivity in reward and effort related brain networks, and measures of effort in patients and pain free controls. Consistent with the hypothesis of "negative hedonic shift" in chronic pain we observed that CLBP patients are significantly less willing than pain free controls to expend effort to go for high cost/high reward choices and their reported low-back pain intensity predicted increased effort discounting. Furthermore, patients task performance was directly correlated to functional connectivity between the ventral striatum and ventro-medial prefrontal cortex, which are major nodes in the reward processing network. Patients performance was not explained by their self-reported depressive symptoms. Our results present new behavioral evidence characterizing the nature of anhedonia in chronic pain and links it directly to cortico-striatal connectivity highlighting the role of this circuitry in the pathophysiology of chronic pain.

Characterisation of the axon initial segment and intrinsic excitability in the sub-acute phase post-ischemic stroke
Background: Stroke is a leading cause of disability and stroke-induced changes in cortical excitability are thought to impede functional recovery. Identifying cellular targets that contribute to maladaptive excitability holds great potential for the development of therapeutic interventions to improve stroke outcomes. One potential target is the axon initial segment (AIS), the specialised cellular domain where action potentials are initiated. In the acute phase post stroke, neurons in the peri-infarct zone display abnormal AIS structural properties which is assumed to contribute to altered neuronal excitability. However, whether this continues into the sub-acute phase post stroke, a period with heightened plasticity and when physical rehabilitation typically begins is unknown. Methods: We induced a photothrombotic ischemic stroke to the right motor cortex of 13-week-old mice alongside adeno-associated virus labelling of layer 2/3 and layer 5 pyramidal neurons in the peri-infarct zone and contralesional motor cortex. Immunofluorescence staining for Ankyrin-G and whole-cell patch clamp electrophysiology measures were made at 28-days post stroke to assess changes in AIS structure and function. Additionally, we investigated potential hemispheric-, cortical layer-, and sex-dependent differences in AIS and intrinsic excitability properties. Results: We found that normal AIS structure and function are preserved in the sub-acute phase post ischemic stroke. However, we found evidence of reduced input resistance across both hemispheres and reduced evoked spike firing frequency in the peri-infarct zone in both sexes. In addition, we found stroke reduced the evoked spike firing frequencies in the contralesional hemisphere, but only in males. Conclusion: Despite the preservation of normal AIS structure and function in the sub-acute phase post ischemic stroke, cortical pyramidal neuron excitability is reduced through other intrinsic membrane mechanisms. Additionally, we show that changes to neuronal excitability spread to the contralesional hemisphere in males. These findings provide novel insight into the maladaptive changes to neural excitability in the sub-acute phase of ischemic stroke and further highlight the need to develop sex-specific stroke treatments.

High Cognitive Violation of Expectations is Compromised in Cerebellar Ataxia
While traditionally considered a motor structure, the cerebellum is also involved in cognition. However, the underlying cognitive mechanisms through which the cerebellum contributes to evolutionarily novel cognitive abilities remain poorly understood. Another open question is how this structure contributes to a core unifying mechanism across domains. Motivated by the evolutionary principle of neural reuse, we suggest that a successful account of cerebellar contributions to higher cognitive domains will build on the structures established role in motor behaviors. We conducted a series of neuropsychological experiments, assessing selective impairments in participants with cerebellar ataxia (CA) compared to neurotypicals in solving sequential discrete problems. In three experiments, participants were asked to solve symbolic subtraction, alphabet letter transformation, and novel artificial grammar problems, which were expected or unexpected. The CA group exhibited a disproportionate cost when comparing expected problems to unexpected problems, suggesting that the cerebellum is critical for violation of expectations (VE) across tasks. The CA group impairment was not found either when the complexity of the problem increased or in conditions of uncertainty. Together, these results demonstrate a possible causal role for the human cerebellum in higher cognitive abilities. VE might be a unifying cerebellar-dependent mechanism across motor and cognitive domains.

Endogenous gene tagging with FnCas9 to track and sort neural lineages from 3D cortical organoids
Neural lineage tracing, or molecular dissection of lineage-specific brain cell types, is used in many labs to learn how neurons grow and mature. However, these studies depend on the growth and characterization of pure cultures, which takes a long time because of biochemical or fluorescence-based isolation through cell surface markers that overlap. These lineage-specific cells, however, can be efficiently sorted using endogenously expressed, fluorescently labeled marker genes. The labeled cell lines can be used not only to differentiate and purify different types of neurons but also to study the long-term development of neural lineages in two- and three-dimensional development models. In this study, we used an orthogonal Cas protein to generate human embryonic stem cell (hESC) lines with genetically labeled fluorescent barcodes for discrete neural lineages. We use these lines to successfully demonstrate spatial and temporal tracing of DCX-positive neuroblasts and immature neuronal cells within 2D neural cultures and 3D cortical organoids derived from human embryonic stem cells. This allowed the purification of endogenously tagged live neural cells from heterogeneous cortical organoids across multiple stages of development.