bioRxiv Subject Collection: Neuroscience's Journal

Noradrenaline causes a spread of association in the hippocampal cognitive map
The mammalian brain stores relationships between items and events in the world as cognitive maps in the hippocampal system. However, the neural mechanisms that control cognitive map formation remain unclear. Here, using a double-blind study design with a pharmacological intervention in humans, we show that the neuromodulator noradrenaline elicits a significant 'spread of association' across the hippocampal cognitive map. This neural spread of association predicts overgeneralisation errors measured in behaviour, and is predicted by physiological markers for noradrenergic arousal, namely an increase in the pupil dilation response and reduced cortical GABAergic tone. Thus, noradrenaline sets the width of the 'smoothing kernel' for plasticity across the cognitive map. Elevated noradrenaline can allow disparate memories to become linked, introducing potential for distortions in the cognitive map that deviate from direct experience.

Switching on Behavioral and Neural Rhythmicity to Retrieve Memories When the Number of Retained Items Exceeds Four
Even when we experience difficulty in recalling memories, we nevertheless manage to retrieve the target items. However, the neural mechanisms that enable such difficult memory retrieval are unknown. Here, we report an intriguing phenomenon where our nervous system "switches on" behavioral/neural rhythmicity to retrieve memory when the number of candidate items exceeds four. In our experiments, participants learned and retrieved 2-5 color/letter pairs. Analyses of hundreds of reaction times revealed a significant tendency for memory recall to occur at discrete times corresponding to theta-alpha (4-13 Hz) cycles, but only when the number of memorized pairs exceeded four. Electrophysiological data localized theta-alpha rhythmicity around parietal electrodes, a region associated with the long-term memory system. Our findings suggest that neural rhythmicity facilitates memory retrieval when the number of candidate items exceeds four, which is known as the "magical number" corresponding to the limit of human cognitive capacity.

Population-level age effects on the white matter structure subserving cognitive flexibility in the human brain
Cognitive flexibility, a cognition crucial for adaptive behavior, involves multi-scale functioning across several neuronal organization levels. While the neural underpinnings of flexibility have been studied for decades, limited knowledge exist about the structure and differentiation of the white matter subserving brain regions implicated in cognitive flexibility. Neural changes that occur over the lifespan have an impact in the brain white matter organization and, thereby, may alter cognitive flexibility abilities. This study investigates the population-level relationship between cognitive flexibility and macromolecular properties of white matter across two periods of adulthood, aiming to discern how these associations vary over different life stages and brain tracts. A novel method to study age-effects in the brain structure-function associations is proposed. First, the white matter structure implicated in cognitive flexibility was delineated by tracing in the Human Connectome Project tractography template the pathways subserving neural regions derived via meta-analysis of set-shifting. Then, a cohort analysis was performed to characterize related brain features using a subset of the UKBiobank MRI data which has a companion functional/behavioral dataset.1 We found that (1) the wiring of cognitive flexibility is defined by specialized tracts, which present undifferentiated features early in adulthood, and significantly differentiated types in later life. (2) These MRI-derived properties are correlated with individual subprocesses of cognition which intimately relate to the latent construct of cognitive flexibility function (switch, inhibition, and updating).2 (3)In late life, myelin-related homogeneity of specific white matter tracts implicated in cognitive flexibility declines as a function of chronological age, a phenomenon not observed in early life. Our findings support the age-related differentiation of white matter tracts implicated in cognitive flexibility as a natural substrate of brain adaptive function.

Deficiency in transmitter release triggers homeostatic transcriptional changes that increase presynaptic excitability
Weakening of synaptic transmission at the Drosophila larval neuromuscular junction triggers two forms of homeostatic compensation, one that increases the probability of glutamate release per action potential (Pr) and another that increases motoneuron (MN) activity. We investigated the molecular changes in MNs that underlie the increase in MN activity. RNA-seq analysis on MNs whose glutamate release is weakened by knockdown of components of the MN transmitter release machinery reveals a reduction in expression of a group of genes that encode potassium channels and their positive modulators. These results identify a mechanism of compensation for weakened synaptic transmission by MNs, which engages a transcriptional program in those cells to increase firing and, thereby, ensure sufficient locomotory drive.

Chronic social defeat stress induces meningeal neutrophilia via type I interferon signaling
Animal models of stress and stress-related disorders are also associated with blood neutrophilia. The mechanistic relevance of this to symptoms or behavior is unclear. We used cytometry, immunohistochemistry, whole tissue clearing, and single-cell sequencing to characterize the meningeal immune response to chronic social defeat (CSD) stress in mice. We find that chronic, but not acute, stress causes meningeal neutrophil accumulation, and CSD increases neutrophil trafficking in vascular channels emanating from skull bone marrow (BM). Transcriptional analysis suggested CSD increases type I interferon (IFN-I) signaling in meningeal neutrophils. Blocking this pathway via the IFN-I receptor (IFNAR) protected against the anhedonic and anxiogenic effects of CSD stress, potentially through reduced infiltration of IFNAR+ neutrophils into the meninges from skull BM. Our identification of IFN-I signaling as a putative mediator of meningeal neutrophil recruitment may facilitate development of new therapies for stress-related disorders.

Neuronal firing rate diversity lowers the dimension of population covariability
Populations of neurons produce activity with two central features. First, neuronal responses are very diverse -- specific stimuli or behaviors prompt some neurons to emit many action potentials, while other neurons remain relatively silent. Second, the trial-to-trial fluctuations of neuronal response occupy a low dimensional space, owing to significant correlations between the activity of neurons. These two features define the quality of neuronal representation. We link these two aspects of population response using a recurrent circuit model and derive the following relation: the more diverse the firing rates of neurons in a population, the lower the effective dimension of population trial-to-trial covariability. This surprising prediction is tested and validated using simultaneously recorded neuronal populations from numerous brain areas in mice, non-human primates, and in the motor cortex of human participants. Using our relation we present a theory where a more diverse neuronal code leads to better fine discrimination performance from population activity. In line with this theory, we show that neuronal populations across the brain exhibit both more diverse mean responses and lower-dimensional fluctuations when the brain is in more heightened states of information processing. In sum, we present a key organizational principle of neuronal population response that is widely observed across the nervous system and acts to synergistically improve population representation.

The human hippocampus is involved in implicit motor learning
Recent evidence suggests that the human hippocampus, traditionally associated with declarative memory, plays a role in motor sequence learning (MSL). However, the classic MSL paradigm depends initially on declarative learning. Therefore, it is critical to discern whether the participation of the hippocampus relates to its canonical role or to processing a general aspect of learning that transcends the declarative/non-declarative distinction. To address this issue, here we turn to visuomotor adaptation -a type of motor learning involving skill recalibration- which unlike MSL can be easily manipulated to eliminate the explicit component. Here, we examined the broader involvement of the hippocampus in procedural motor learning by using diffusion MRI to indirectly assess structural plasticity associated with memory consolidation in visuomotor adaptation (VMA) and an implicit-only version (IVMA). We found that both VMA and IVMA engaged the left posterior hippocampus in a learning-specific manner. Remarkably, while VMA induced only transient hippocampal alterations, IVMA elicited structural changes that persisted overnight, underscoring the reliance on implicit learning for enduring neuroplasticity. As expected, training on both visuomotor tasks impacted the microstructure of the cerebellum, the motor and the posterior parietal cortex. Notably, the temporal dynamics of changes in these regions closely paralleled those of the left hippocampus, suggesting that motor and limbic regions operate in a coordinated manner as part of the same neural network. Collectively, our findings support an active role of the hippocampus in procedural motor memory and argue for a unified function in memory encoding regardless of the declarative or non-declarative nature of the task.

The impact of language proficiency on task-dependent neural activity and functional connectivity: Insights from deafness
Our study aimed to investigate the impact of differences in language proficiency on the neural correlates of cognitive processing in deaf adults. In congenitally and early deaf individuals, individual differences in language proficiency reflect the degree of language access during critical developmental periods and significantly influence cognitive function. By studying the neural substrates of cognition in a population with diverse language backgrounds and skills, we can explore the influence of early language experience on the formation of cognitive networks in the brain. We used functional MRI in a group of deaf adults with varying language experience backgrounds and a control group of hearing participants. In this study, we investigated the hypothesis that differences in language skills modulate neural response and functional connectivity during the execution of demanding cognitive tasks tapping into working memory and planning. Our study revealed that differences in language proficiency, independently of language modality (signed or spoken), are positively correlated with neural activity and functional connectivity within regions of the task-positive network during working memory in deaf adults. Furthermore, compared to hearing participants, the deaf group showed distinctive patterns of neural activity and connectivity during working memory task performance in task-dependent regions of the brain. Taken together, our findings emphasise the profound impact of early environmental experiences on brain responses during cognitive processing. Specifically, they highlight the role of language proficiency in shaping and supporting high-order cognition in the brain.

CHCHD2 mutant mice display mitochondrial protein accumulation and disrupted energy metabolism
Mutations in the mitochondrial cristae protein CHCHD2 lead to a late-onset autosomal dominant form of Parkinson's disease (PD) which closely resembles idiopathic PD, providing the opportunity to gain new insights into the mechanisms of mitochondrial dysfunction contributing to PD. To begin to address this, we used CRISPR genome-editing to generate CHCHD2 T61I point mutant mice. CHCHD2 T61I mice had normal viability, and had only subtle motor deficits with no signs of premature dopaminergic (DA) neuron degeneration. Nonetheless, CHCHD2 T61I mice exhibited robust molecular changes in the brain including increased CHCHD2 insolubility, accumulation of CHCHD2 protein preferentially in the substantia nigra (SN), and elevated levels of -synuclein. Metabolic analyses revealed an increase in glucose metabolism through glycolysis relative to the TCA cycle with increased respiratory exchange ratio, and immune-electron microscopy revelated disrupted mitochondria in DA neurons. Moreover, spatial genomics revealed decreased expression of mitochondrial complex I and III respiratory chain proteins, while proteomics revealed increased respiratory chain and other mitochondrial protein-protein interactions. As such, the CHCHD2 T61I point-mutation mice exhibit robust mitochondrial disruption and a consequent metabolic shift towards glycolysis. These findings thus establish CHCHD2 T61I mice as a new model for mitochondrial-based PD, and implicate disrupted respiratory chain function as a likely causative driver.

Validation studies and multi-omics analysis of Zhx2 as a candidate quantitative trait gene underlying brain oxycodone metabolite (oxymorphone) levels and behavior
Sensitivity to the subjective reinforcing properties of opioids has a genetic component and can predict addiction liability of opioid compounds. We previously identified Zhx2 as a candidate gene underlying increased brain concentration of the oxycodone (OXY) metabolite oxymorphone (OMOR) in BALB/cJ (J) versus BALB/cByJ (By) females that could increase OXY state-dependent reward. A large structural intronic variant is associated with a robust reduction of Zhx2 expression in J mice, which we hypothesized enhances OMOR levels and OXY addiction-like behaviors. We tested this hypothesis by restoring the Zhx2 loss-of-function in Js (MVKO) and modeling the loss-of-function variant through knocking out the Zhx2 coding exon (E3KO) in Bys and assessing brain OXY metabolite levels and behavior. Consistent with our hypothesis, Zhx2 E3KO females showed an increase in brain OMOR levels and OXY-induced locomotor activity. However, contrary to our hypothesis, state-dependent expression of OXY-CPP was decreased in E3KO females and increased in E3KO males. We also overexpressed Zhx2 in the livers and brains of Js and observed Zhx2 overexpression in select brain regions that was associated with reduced OXY state-dependent learning. Integrative transcriptomic and proteomic analysis of E3KO mice identified astrocyte function, cell adhesion, extracellular matrix properties, and endothelial cell functions as pathways influencing brain OXY metabolite concentration and behavior. These results support Zhx2 as a quantitative trait gene underlying brain OMOR concentration that is associated with changes in OXY behavior and implicate potential quantitative trait mechanisms that together inform our overall understanding of Zhx2 in brain function.

Target Identification Under High Levels of Amplitude, Size, Orientation and Background Uncertainty
Many natural tasks require the visual system to classify image patches accurately into target categories, including the category of no target. Natural target categories often involve high levels of within-category variability (uncertainty), making it challenging to uncover the underlying computational mechanisms. Here, we describe these tasks as identification from a set of exhaustive, mutually exclusive target categories, each partitioned into mutually exclusive subcategories. We derive the optimal decision rule and present a computational method to simulate performance for moderately large and complex tasks. We focus on the detection of an additive wavelet target in white noise with five dimensions of stimulus uncertainty: target amplitude, orientation, scale, background contrast, and spatial pattern. We compare the performance of the ideal observer with various heuristic observers. We find that a properly normalized heuristic MAX observer (SNN-MAX) approximates optimal performance. We also find that a convolutional neural network trained on this task approaches but does not reach optimal performance, even with extensive training. We measured human performance on a task with three of these dimensions of uncertainty (orientation, scale, and background pattern). Results show that the pattern of hits and correct rejections for the ideal and SNN-MAX observers (but not a simple MAX observer) aligns with the data. Additionally, we measured performance under low uncertainty (without scale and orientation uncertainty) and found that the effect of uncertainty on the performance is smaller than any of the models predicted. This smaller-than-expected effect can largely be explained by including biologically plausible levels of intrinsic position uncertainty.

Acetylcholine modulates prefrontal outcome coding during threat learning under uncertainty
Outcomes can vary even when choices are repeated. Such ambiguity necessitates adjusting how much to learn from each outcome by tracking its variability. The medial prefrontal cortex (mPFC) has been reported to signal the expected outcome and its discrepancy from the actual outcome (prediction error), two variables essential for controlling the learning rate. However, the source of signals that shape these coding properties remains unknown. Here, we investigated the contribution of cholinergic projections from the basal forebrain because they carry precisely timed signals about outcomes. One-photon calcium imaging revealed that as mice learned different probabilities of threat occurrence on two paths, some mPFC cells responded to threats on one of the paths, while other cells gained responses to threat omission. These threat- and omission-evoked responses were scaled to the unexpectedness of outcomes, some exhibiting a reversal in response direction when encountering surprising threats as opposed to surprising omissions. This selectivity for signed prediction errors was enhanced by optogenetic stimulation of local cholinergic terminals during threats. The enhanced threat-evoked cholinergic signals also made mice erroneously abandon the correct choice after a single threat that violated expectations, thereby decoupling their path choice from the history of threat occurrence on each path. Thus, acetylcholine modulates the encoding of surprising outcomes in the mPFC to control how much they dictate future decisions.

Neural Basis of Number Sense in Larval Zebrafish
Number sense, the ability to discriminate the quantity of objects, is crucial for survival. To understand how neurons work together and develop to mediate number sense, we used two-photon fluorescence light sheet microscopy to capture the activity of individual neurons throughout the brain of larval zebrafish (Danio rerio), while displaying a visual number stimulus to the animal. We identified number-selective neurons as early as 3 days post-fertilization (dpf) and found a proportional increase of neurons tuned to larger (>2) quantities after 3 dpf. To determine if these neurons are sufficient to encode the correct quantity, we used machine learning to predict the stimulus from the neuronal activity and observed that the prediction accuracy improves with age. Given ethanol's propensity to inhibit cognitive functions, we tested its effect on number sense and found a decrease of active number-selective neurons in the forebrain during ethanol exposure, suggesting cognitive impairment. The findings here are a significant step towards understanding neural circuits devoted to discrete magnitudes and our methodology to track single neuron activity across the whole brain is broadly applicable to other fields in neuroscience.

Differential coding of fruit, leaf, and microbial odours in the brains of Drosophila suzukii and Drosophila melanogaster.
The fly Drosophila suzukii, a close relative of D. melanogaster severely damages the production of berry and stone fruits in large parts of the world. Unlike D. melanogaster, which reproduces on overripe and fermenting fruits on the ground, D. suzukii prefers to lay its eggs in ripening fruits still on the plants. Flies locate fruit hosts by their odorant volatiles, which are detected and encoded by a highly specialized olfactory system before being translated into behaviour. The exact information processing pathway is not yet fully understood, especially the evaluation of odour attractiveness. It is also unclear what differentiates the brains of D. suzukii and D. melanogaster to cause the crucial difference in host selection. We hypothesized that the basis for different behaviours is already formed at the level of the antennal lobe of D. suzukii and D. melanogaster, by different neuronal responses to volatiles associated with ripe and fermenting fruit. We thus investigated by 3D in vivo two-photon calcium imaging how both species encoded odours from ripe fruits, leaves, fermented fruits, bacteria, and their mixtures in the antennal lobe. We then assessed their behavioural responses to mixtures of ripe and fermenting odours. The neural responses reflect species-dependent shifts in the odour code. In addition to this, morphological differences were also observed. Yet this was not directly reflected in different behavioural responses to the odours tested.

Elimination of the neuroparsin neuroendocrine cells in Drosophila virilis using the UAS-Gal4 system shows that neuroparsin is not important for reproduction in this species.
Neuroparsin is a common insect neurohormone produced in large neuroendocrine cells in the brain and is important in mosquito reproduction. Although it is present in many flies including many Drosophila species, it was lost from D. melanogaster and a few closely related species. Three different lines of transgenic D. virilis were produced: One that expresses the yeast transcription factor gal4 under the control of the neuroparsin promoter (NP-gal4), while others codes for proteins under the control of the gal4 promoter, either enhanced green fluorescent protein (UAS-eGFP) or the D. virilis ortholog of reaper, an apoptosis inducing protein (UAS-rpr). Crosses between UAS-eGFP and NP-gal4 revealed that expression of NP-gal4 was correct. Crosses between UAS-rpr and NP-gal4 completely eliminated the neuroparsin neuroendocrine cells, but were without effect on reproduction.

Chronic mitochondrial fragmentation elicits a neuroprotective Warburg-like effect in Drosophila neurons
Mitochondrial fission and fusion are dynamic and important cellular processes, but the roles of these two very different mitochondrial forms, predominantly spherical and tubular are not well-characterized in neurons of animals and especially in aging neurons. This is important because neurons are long-lived and mitochondrial dynamics is associated with neurodegenerative diseases. We used here an efficient cell type-specific CRISPR approach to knockout key fission-fusion genes and disrupt mitochondrial dynamics within the inessential clock neurons of Drosophila. Surprisingly, fusion is much more important than fission for maintaining long-term neuronal function. Neurons survive chronic mitochondrial fragmentation due to loss of fusion by triggering a cancer-like transcriptomic response. This Warburg effect includes ATF4-mediated upregulation of the aerobic glycolysis gene Lactate dehydrogenase (Ldh), and LDH is essential to prevent neurodegeneration of neurons deficient in the fusion gene Opa1. These results and others provide insights into the intersection of neuronal metabolism, aging and neurodegeneration.

Unbiased preclinical phenotyping reveals neuroprotective properties of pioglitazone
Animal models are essential for assessing the preclinical efficacy of candidate drugs, but animal data often fails to replicate in human clinical trials. This translational gulf is due in part to the use of models that do not accurately replicate human disease processes and phenotyping strategies that do not capture sensitive, disease-relevant measures. To address these challenges with the aim of validating candidate neuroprotective drugs, we combined a mouse prion (RML scrapie) model that recapitulates the key common features of human neurodegenerative disease including bona fide neuronal loss, with unbiased and machine learning-assisted behavioural phenotyping. We found that this approach measured subtle, stereotyped, and progressive changes in motor behaviour over the disease time course that correlated with the earliest detectable histopathological changes in the mouse brain. To validate the utility of this model system, we tested whether the anti-diabetic drug pioglitazone could slow prion disease progression. Pioglitazone crosses the blood-brain-barrier and has been shown to reduce neurodegenerative disease severity in other mouse models. We found that in addition to significantly slowing the emergence of early-stage clinical signs of neurodegeneration, pioglitazone significantly improved motor coordination throughout the disease time course and reduced neuronal endoplasmic reticulum stress. Together, these findings suggest that pioglitazone could have neuroprotective properties in humans, confirm the utility of the scrapie mouse model of neurodegeneration, and provide generalisable experimental and analysis methods for the generation of data-rich behavioural data to accelerate and improve preclinical validation.

Estimating the Excitatory-Inhibitory Balance from Electrocorticography Data using Physics-Informed Neural Networks
Understanding the excitatory/inhibitory (E/I) balance in the brain is crucial for elucidating the neural mechanisms underlying various cognitive functions and states of consciousness. Mathematical models have provided significant insights into these mechanisms, but they often face challenges due to high dimensionality, noisy observation signals, and nonlinearities. In this paper, we introduce a novel methodology using Physics-Informed Neural Networks (PINNs) to estimate the E/I balance from electrocorticography (ECoG) data, effectively addressing these limitations. By integrating physical laws via a neural mass model with neural network training, our approach enhances parameter estimation accuracy and robustness. Our analysis reveals a significant reduction in long-range connections (LRCs) and excitatory short-range connections (SRCs) under anesthesia, alongside an increase in inhibitory SRCs, highlighting anesthesia's role in modulating neural dynamics to induce unconsciousness. These findings not only corroborate existing theories on the neural mechanisms of anesthesia but also provide new insights into brain connectivity and its relationship with consciousness.

Synaptic imbalance and increased inhibition impair motor function in SMA
Movement is executed through the balanced action of excitatory and inhibitory neurotransmission in motor circuits of the spinal cord. Short-term perturbations in one of the two types of transmission are counteracted by homeostatic changes of the opposing type. Prolonged failure to balance excitatory and inhibitory drive results in dysfunction at the single neuron, as well as neuronal network levels. However, whether dysfunction in one or both types of neurotransmission leads to pathogenicity in neurodegenerative diseases characterized by select synaptic deficits is not known. Here, we used mouse genetics, functional assays, morphological methods, and viral-mediated approaches to uncover the pathogenic contribution of unbalanced excitation-inhibition neurotransmission in a mouse model of spinal muscular atrophy (SMA). We show that vulnerable motor circuits in the SMA spinal cord fail to respond homeostatically to the reduction of excitatory drive and instead increase inhibition. This imposes an excessive burden on motor neurons and further restricts their recruitment to activate muscle contraction. Importantly, genetic or pharmacological reduction of inhibitory synaptic drive improves neuronal function and provides behavioural benefit in SMA mice. Our findings identify the lack of excitation-inhibition homeostasis as a major maladaptive mechanism in SMA, by which the combined effects of reduced excitation and increased inhibition diminish the capacity of premotor commands to recruit motor neurons and elicit muscle contractions.