bioRxiv Subject Collection: Neuroscience's Journal

Comparing Automated Subcortical Volume Estimation Methods; Amygdala Volumes Estimated by FSL and FreeSurfer Have Poor Consistency
Subcortical volumes are a promising source of biomarkers and features in biosignatures, and automated methods facilitate extracting them in large, phenotypically rich datasets. However, while extensive research has verified that the automated methods produce volumes that are similar to those generated by expert annotation, the consistency of methods with each other is understudied. Using data from the UK Biobank, we compare the estimates of subcortical volumes produced by two popular software suites: FSL and FreeSurfer. Although most subcortical volumes exhibit good to excellent consistency across the methods, the tools produce diverging estimates of amygdalar volume. Through simulation, we show that this poor consistency can lead to conflicting results, where one but not the other tool suggests statistical significance, or where both tools suggest a significant relationship but in opposite directions. Considering these issues, we discuss several ways in which care should be taken when reporting on relationships involving amygdalar volume.

Morphology, but not microtubules, of the retinal nerve fibers are protected by nicotinamide in glaucoma mice
Glaucoma is a blinding disease where the retinal ganglion cells (RGCs) and the axons degenerate. Degradation of axonal microtubules is thought to play a critical role in the pathogenesis, but the mechanism is unknown. Here we investigate whether microtubule disruption in glaucoma can be alleviated by metabolic rescue. Using nicotinamide to reduce metabolic stress, the morphology and integrity of microtubules of the retinal nerve fibers are examined in a mouse model of glaucoma, DBA/2. Surprisingly, we found that morphology but not microtubules are protected by the dietary supplement of nicotinamide. Co-registered second-harmonic generation and immunofluorescence images shows that microtubule deficit is not due to a shortage of tubulins and colocalizes with the sectors in which RGCs are disconnected from the brain, indicating that the instability of axonal microtubules may underlie axonal transport deficit in glaucoma. Together, our data confirms distinct roles of axonal microtubules in glaucomatous degeneration, offering a new opportunity for neuroprotection.

SAMson: an automated brain extraction tool for rodents using SAM
Brain extraction, i.e. the precise removal of MRI signal outside the brain boundaries, is a key step in MRI preprocessing pipelines, typically achieved via masks delineating the region of interest (ROI). Existing automated tools often lack accuracy for rodent MRI due to resolution limitations, so large manual editing efforts are required. This work introduces SAMson, a high-precision automated mask generator built on Meta AI's Segment-Anything Model (SAM). SAM's adaptability to diverse tasks, akin to other foundation models (Chat-GPT), is harnessed to address the scarcity of training data in this domain. SAMson is a Python-based tool that integrates SAM's capabili-ties with the requirements and characteristics of multislice MRI data. SAM-son offers two prompt generation approaches: Semi-Auto, enabling manual prompt selection for precise control, and Full-Auto, with automated prompt generation. Evaluation against gold-standard masks extracted by an experi-enced experimenter demonstrated excellent performance of SAMson, and benchmarking against established methods (BET from FSL) demonstrated SAMson's superiority. Robustness assessments on datasets obtained from an external MRI facility, confirmed versatility across scanner setups and image resolutions. Our tool's adaptability and performance underscore its potential for widespread adoption in rodent MRI research, supported by open-source availability for the scientific community.

Altered circadian rhythm, sleep, and rhodopsin 7-dependent shade preference during diapause in Drosophila melanogaster
To survive adverse environments, many animals enter a dormant state such as hibernation, dauer, or diapause. Various Drosophila species undergo adult reproductive diapause in response to cool temperatures and/or short day-length. While it is known that flies are less active during diapause, an in-depth understanding of diapause effects on circadian rhythms and sleep is lacking. Here we show that, in diapause-inducing conditions, Drosophila melanogaster exhibit altered circadian activity profiles, including a severely reduced morning activity peak and an advanced evening activity peak. Consequently, the flies have a single activity peak at a time similar to when non-diapausing flies have a siesta. Temperatures [≤]15{degrees}C, rather than short day-length, primarily drive the behavior. At cool temperatures, flies also rapidly enter a deep sleep state that lacks the sleep cycles of flies at higher temperatures and requires particularly high levels of stimulation for arousal. Furthermore, we show that at 18-25{degrees}C, flies prefer to siesta in the shade, a preference that is virtually eliminated at 10{degrees}C. Resting in the shade is driven by an aversion to blue light, sensed by rhodopsin 7 (Rh7) outside of the eyes. Flies at 10 {ring}C show neuronal markers of elevated sleep pressure, including increased expression of Bruchpilot and elevated Ca2+ in the R5 ellipsoid body neurons. Therefore sleep pressure might overcome blue light aversion. Thus at temperatures known to cause reproductive arrest, preserve germline stem cells, and extend lifespan, Drosophila melanogaster are prone to deep sleep and exhibit dramatically altered - yet rhythmic - daily activity patterns.

TREM1 disrupts myeloid bioenergetics and cognitive function in aging and Alzheimer disease models
Human genetics implicate defective myeloid responses in the development of late onset, age-associated Alzheimer disease (AD). Aging is characterized by a decline in myeloid metabolism that triggers maladaptive, neurotoxic immune responses. TREM1 is an amplifier of pro-inflammatory myeloid responses, and here we find that Trem1 deficiency prevents age-dependent changes in myeloid metabolism, inflammation, and hippocampal memory function. Trem1 deficiency rescues age-associated declines in ribose-5P, a glycolytic intermediate and the precursor for purine, pyrimidine, and NAD+ biosynthesis. In vitro, Trem1 deficient microglia are resistant to bioenergetic changes induced by amyloid-beta 42 oligomers (Abeta42), suggesting that Abeta42 stimulation disrupts homeostatic microglial metabolism and immune function via TREM1. In the 5XFAD model of amyloid accumulation, Trem1 haploinsufficiency prevents spatial memory loss, preserves homeostatic microglial morphology, and reduces neuritic dystrophy independent of amyloid accumulation or changes in the disease-associated microglial transcriptomic signature. In aging APPSwe mice, Trem1 deficiency restores synaptic mitochondrial function and cerebral glucose uptake and prevents hippocampal memory decline. In post-mortem human brain, microglial TREM1 expression increases with clinical and neuropathological severity. Thus, TREM1-mediated disruption of myeloid metabolism, both in the periphery and brain, promotes cognitive decline in aging and amyloid accumulation, two major risk factors for AD development.

Single molecule fingerprinting reveals different growth mechanisms in seed amplification assays for different polymorphs of alpha Synuclein fibrils.
Alpha-synuclein (aSyn) aggregates, detected in the biofluids of patients with Parkinsons disease, have the ability to catalyze their own aggregation, leading to an increase in the number and size of aggregates. This self-templated amplification is used by newly developed assays to diagnose Parkinsons disease and turned the presence of aSyn aggregates into a biomarker of the disease. It has become evident that aSyn can form fibrils with slightly different structures, called strains or polymorphs, but little is known about their differential reactivity in diagnostic assays. Here we compared the properties of two well-described aSyn polymorphs. Using single molecule techniques, we observed that one of the polymorphs had an increased tendency to undergo secondary nucleation and we showed that this could explain the differences of reactivity observed in in vitro seed amplification assay and cellular assays. Simulations and high-resolution microscopy suggest that a 100-fold difference in apparent rate of growth can be generated by a surprisingly low number of secondary nucleation points (1 every 2,000 monomers added by elongation). When both strains are present in the same seeded reaction, secondary nucleation displaces proportions dramatically and causes a single strain to dominate the reaction as the major end-product.

Persistent cognitive deficits in anti-LGI1 encephalitis are linked to a reorganization of structural brain networks
Importance: Despite immunotherapy, most patients with anti-leucine-rich, glioma-inactivated 1 encephalitis (LGI1-E) develop long-term cognitive deficits that persist for years after peak illness. However, the structural brain changes that underlie these deficits remain poorly understood. Objective: To study the relationship between cognitive outcomes and white matter (WM) networks in LGI1-E. Design & Setting: Cross-sectional study. German university center. Participants: 25 patients with LGI1-E (19/25 male [76%], mean age: 63 {+/-} 12 years) and 25 age- and sex-matched healthy controls (HC), recruited between January 2013 and April 2019. Main Outcomes and Measures: Clinical assessments including the modified Rankin Scale (mRS) and Clinical Assessment Scale in Autoimmune Encephalitis (CASE); comprehensive cognitive testing; WM tractography using diffusion-weighted MRI. Results: All patients had received first-line immunotherapy, and two-thirds underwent second-line immunotherapy. Patients showed a significant reduction in mRS scores from peak illness to post-acute follow-up (z = -3.8, p < 0.001, n = 20), with 85% presenting "good" functional outcomes (post-acute mRS [≤] 2), paralleled by a significant reduction in CASE scores (z = -3.5, p < 0.001, n = 20). Despite this overall improvement, however, cognitive symptoms were highly prevalent at peak illness (95% of patients affected) and strongly persisted into the post-acute disease stage (85% affected). Neuroimaging at post-acute follow-up (median: 12 months from onset) revealed that LGI1-E is characterized by (i) significantly reduced whole-brain structural connectivity (t = -2.16, p = 0.036, d = -0.61), (ii) a cortico-subcortical hypoconnectivity cluster that strongly affects the hippocampus but also severely impacts extra-limbic brain systems, (iii) systematic limbic and extra-limbic decreases in node degree -- a graph-theoretical measure of overall connectedness, and (iv) a "topological reorganization" of structural brain networks, marked by a bidirectional shift in the relative importance of individual brain regions in the network. Importantly, the extent of this network reorganization was significantly related to persistent cognitive deficits in the domains of verbal memory (r = -0.57, p = 0.007, n = 21), attention (r = -0.47, p = 0.030, n = 21), and executive functions (r = -0.60, p = 0.010, n = 17). Conclusion and Relevance: This study characterizes LGI1-E as a network disease that affects both limbic and extra-limbic brain systems and shows that a reorganization of WM networks is linked to multi-domain cognitive deficits in the post-acute disease stage -- despite immunotherapy and good overall recovery. These findings highlight the need for extended treatment strategies to improve long-term cognitive outcomes and propose a sensitive new neuroimaging marker to include in prospective clinical trials.

Normative models combining fetal and postnatal MRI data to characterize neurodevelopmental trajectories during the transition from in- to ex-utero
The perinatal period involves transitioning from an intra- to an extrauterine environment, which requires a complex adaptation of the brain. This period is marked with dynamic and multifaceted cortical changes in both structure and function. Most studies to date have focused either on the fetal or postnatal period, independently. To the best of our knowledge, this is the first neurodevelopmental study targeting the cortical trajectory of typically developing perinatal subjects, combining MRIs from both fetal and postnatal participants. Prior to analysis, preprocessing and segmentation parameters were harmonized across all subjects in order to overcome methodological limitations that arise when studying such different populations. We conducted a normative modeling analysis on a sample of 607 subjects, age ranged 24 to 45 weeks post-conception, to observe changes that arise as participants traverse the birth barrier. We observed that the trajectories of global surface area and several volumetric features, including total gray matter, white matter, brainstem, cerebellum and hippocampi, follow distinct but continuous patterns during this transition. We further report three features presenting a discontinuity in their neurodevelopmental trajectories as participants traverse from a fetal to a postnatal environment: the extra-cerebrospinal fluid volume, the ventricular volume and global gyrification. The current study demonstrates the presence of unique neurodevelopmental patterns for several structural features during the perinatal period, and confirms that not all features are affected in the same way as they cross the birth barrier.

Role of the right middle occipital gyrus in egocentric spatial orientation in reference to gravitational information: Evidence from a pre-registered rTMS study
Accurate perception of the orientation of external objects relative to the body, known as egocentric spatial orientation, is fundamental to action. Previously, we found via behavioral and magnetic resonance imaging voxel-based morphometry studies that egocentric spatial orientation is distorted when the whole body is tilted with respect to gravity, and that the magnitude of this perceptual distortion is correlated with grey matter volume in the right middle occipital gyrus (rMOG). In the present pre-registered study, we demonstrated that neural processing in the rMOG is indeed a cause of the perceptual distortion. We transiently suppressed neural activity in the rMOG by applying low-frequency repetitive transcranial magnetic stimulation (rTMS) and evaluated the consequent effect on perceptual distortion. Our results showed that while rTMS over the rMOG significantly reduced perceptual distortion when the body was tilted with respect to gravity, it did not affect egocentric spatial orientation when in the upright position. No changes in perceptual distortion were observed when rTMS was applied to a control site (right temporoparietal junction) or to air (sham TMS). These results indicate that neural processing in the rMOG during body tilt is an essential cause of perceptual distortion, suggesting that the rMOG is engaged in egocentric spatial orientation concerning gravitational information.

Methodological choices matter: A systematic comparison of TMS-EEG studies targeting the primary motor cortex
Background: Transcranial magnetic stimulation (TMS) triggers time-locked cortical activity that can be recorded with electroencephalography (EEG). Transcranial evoked potentials (TEPs) are widely used to probe brain responses to TMS. Methods: Here, we systematically reviewed 137 published experiments that studied TEPs elicited from TMS to the human primary motor cortex (M1) in healthy individuals to investigate the impact of methodological choices. We scrutinized prevalent methodological choices and assessed how consistently they were reported in published papers. We extracted amplitudes and latencies from reported TEPs and compared total cortical activation and specific TEP peaks and components. Results: Reporting of methodological details was overall sufficient, but some relevant information regarding the TMS settings and the recording and pre-processing of EEG data were missing in more than 25% of the included experiments. The published TEP latencies and amplitudes confirm the "prototypical" TEP waveform of M1, comprising distinct N15, P30, N45, P60, N100, and P180 peaks. However, variations in amplitude and latencies were evident across studies. Higher stimulation intensities were associated with overall larger TEP amplitudes. Active noise masking during TMS generally resulted in lower TEP amplitudes compared to no or passive masking but did not specifically impact those TEP peaks linked to long-latency sensory processing. Studies implementing independent component analysis (ICA) for artifact removal generally reported lower TEP amplitudes. Conclusion: Some aspects of reporting practices could be improved in TEP studies to enable replication. Methodological choices, including TMS intensity and the use of noise masking or ICA, introduce systematic differences in reported TEP amplitudes. Further investigation into the significance of these and other methodological factors and their interactions is warranted.

Cognitive modeling of the Mnemonic Similarity Task as a digital biomarker for Alzheimer's Disease
AD related pathologies, such as beta-amyloid (A{beta}) and phosphorylated tau (pTau), are evident decades before any noticeable decline in memory occurs. Identifying individuals during this asymptomatic phase is crucial for timely intervention. The Mnemonic Similarity Task (MST), a modified recognition memory task, is especially relevant for early AD screening, as it assesses hippocampal integrity, a region affected (both directly and indirectly) early in the progression of the disease. Further, strong inferences on the underlying cognitive mechanisms that support performance on this task can be made using Bayesian cognitive modeling. We assessed whether analyzing MST performance using a cognitive model could detect subtle changes in cognitive function and AD biomarker status prior to overt cognitive decline. We analyzed MST data from >200 individuals (young, cognitively healthy older adults, and individuals with MCI), a subset of which also had existing CSF A{beta} and pTau data. Traditional performance scores and cognitive modeling using multinomial processing trees was applied to each participants MST data using Bayesian approach-es. We assessed how well each could predict age group, memory ability, MCI status, A{beta}/pTau sta-tus using ROC analyses. Both approaches predicted age group membership equally, but cognitive modeling approaches exceeded traditional metrics in all other comparisons. This work establishes that cognitive modeling of the MST can detect individuals with AD prior to cognitive decline, making it a potentially useful tool for both screening and monitoring older adults during the asymptomatic phase of AD.

Making Moral Decisions With Artificial Agents As Advisors. An fNIRS Study
Artificial Intelligence (AI) is on the verge of impacting every domain of our life. It is now being increasingly used as an advisor to help make (moral) decisions. The present study aimed at investigating the influence of moral arguments provided by AI-advisors (i.e., decision aid tool) on human moral decision-making and the associated neural correlates. Participants were presented with utilitarian and deontological sacrificial moral dilemmas and had to make moral decisions either by themselves (i.e., baseline run) or with AI-advisors that provided either utilitarian or deontological advice (i.e., AI-advised run), while their brain activity was measured using an fNIRS device. Overall, AI-advisors significantly influenced participants, who often modified their decisions according to AI-advisors arguments. Longer response times and a decrease in right dorsolateral prefrontal cortex activity were observed in response to deontological arguments than to utilitarian arguments. Besides triggering a conflict in participants, being provided with deontological arguments by machine appears to have led to a decreased appraisal of the affective response to the dilemmas. This resulted in a reduced level of utilitarianism, supposedly in an attempt to avoid behaving more like a machine than the machines themselves. Taken together, these results contradict Greene s moral dual-process theory and suggest that motivational power can led to a voluntary up- and down- regulation of affective reactions.

Dopamine dynamics in chronic pain: music-induced sex-dependent behavioral effects in mice
Chronic pain is a debilitating disease that is usually comorbid to anxiety and depression. Current treatment approaches primarily rely on analgesics, but they often neglect emotional aspects. Non-pharmacological interventions have been incorporated into clinics to provide a more comprehensive management of chronic pain. Among these interventions, listening to music is a well-accepted and cost-effective option. However, the underlying mechanisms of music-mediated pain relief remain insufficiently understood. Here, our aim was to evaluate the effects of music exposure in an animal model of chronic pain. First, we injected mice with the inflammatory agent complete Freund adjuvant (CFA) into the hind paw and housed them for 14 days with background music during their active period (Mozart K.205, overnight), or silence. The impact of music exposure on nociception and anxiety-like and depression-like behaviors was evaluated through different paradigms, including the hot plate, Von Frey, elevated plus maze, splash, and tail suspension tests. Additionally, we investigated whether music influences dopamine dynamics in the nucleus accumbens (NAcc), a pivotal region involved in pain processing, anhedonia, and reward. Our findings indicate that music exposure prevents the decreased NAcc activity observed in CFA-injected mice, linking with a sex-dependent reduction of allodynia, anxiety- and depression-like behaviors. Thus, females were more sensitive to music exposure. Collectively, our findings provide compelling evidence for the integration of music listening as a non-pharmacological intervention in chronic pain conditions. Moreover, the observed impact on the NAcc suggests its potential as a therapeutic target for addressing chronic pain and its associated symptoms.

Beta bursts in the parkinsonian cortico-basal ganglia network form spatially discrete ensemble.
Defining spatial synchronization of pathological beta oscillations is important, given that many theories linking them to parkinsonian symptoms propose a reduction in the dimensionality of the coding space within and/or across cortico-basal ganglia structures. Such spatial synchronization could arise from a single process, with widespread entrainment of neurons to the same oscillation. Alternatively, the partially segregated structure of cortico-basal ganglia loops could provide a substrate for multiple ensembles that are independently synchronized at beta frequencies. Addressing this question requires an analytical approach that identifies groups of signals with a statistical tendency for beta synchronisation, which is unachievable using standard pairwise measures. Here, we utilized such an approach on multichannel recordings of background unit activity (BUA) in the external globus pallidus (GP) and subthalamic nucleus (STN) in parkinsonian rats. We employed an adapted version of a principle and independent component analysis-based method commonly used to define assemblies of single neurons (i.e., neurons that are synchronized over short timescales). This analysis enabled us to define whether changes in the power of beta oscillations in local ensembles of neurons (i.e., the BUA recorded from single contacts) consistently covaried over time, forming a beta ensemble. Multiple beta ensembles were often present in single recordings and could span brain structures. Membership of a beta ensemble predicted significantly higher levels of short latency (<5ms) synchrony in the raw BUA signal and phase synchronization with cortical beta oscillations, suggesting that they comprised clusters of neurons that are functionally connected at multiple levels, despite sometimes being non-contiguous in space. Overall, these findings suggest that beta oscillations do not comprise a single synchronization process, but rather multiple independent activities that can bind both spatially contiguous and non-contiguous pools of neurons within and across structures. As previously proposed, such ensembles provide a substrate for beta oscillations to constrain the coding space of cortico-basal ganglia circuits.

Uncertainty-based causal inference modulates audiovisual temporal recalibration
Cross-modal temporal recalibration is crucial for maintaining coherent perception in a multimodal environment. The classic view suggests that cross-modal temporal recalibration aligns the perceived timing of sensory signals from different modalities, such as sound and light, to compensate for physical and neural latency differences. However, this view cannot fully explain the nonlinearity and asymmetry observed in audiovisual recalibration effects: the amount of recalibration plateaus with increasing audiovisual asynchrony and varies depending on the leading modality of the asynchrony during exposure. To address these discrepancies, our study examines the mechanism of audiovisual temporal recalibration through the lens of causal inference, considering the brain's capacity to determine whether multimodal signals come from a common source and should be integrated, or else kept separate. In a three-phase recalibration paradigm, we manipulated the adapter stimulus-onset asynchrony in the exposure phase across nine sessions, introducing asynchronies up to 0.7 s of either auditory or visual lead. Before and after the exposure phase in each session, we measured participants' perception of audiovisual relative timing using a temporal-order-judgment task. We compared models that assumed observers recalibrate to approach either the physical synchrony or the causal-inference-based percept, with uncertainties specific to each modality or comparable across them. Modeling results revealed that a causal-inference model incorporating modality-specific uncertainty captures both the nonlinearity and asymmetry of audiovisual temporal recalibration. Our results indicate that human observers employ causal-inference-based percepts to recalibrate cross-modal temporal perception.

Earlier finish of motor planning in the premotor cortex predicts faster motor command in the primary motor cortex: human intracranial EEG evidence
The human motor system has a hierarchical control during finger movements. The non-primary motor cortex (premotor cortex, PM, and supplementary motor area, SMA) organizes motor planning, while the primary motor cortex (M1) is responsible for motor execution. We utilized the human intracranial EEG to investigate how the temporal dynamics of the high-gamma neural oscillations in the hierarchically organized motor sub-regions, during both pre-movement planning and motor execution, correlated with reaction times (RTs) in a cued finger movement task. Our results showed that the high-gamma power of PM, SMA, and M1 activated sequentially. More importantly, the sustained high-gamma power activation in the non-primary motor cortex and the peak latency of high-gamma power in M1 had a significant predictive relationship with the RTs. In particular, the faster the activation of the non-primary motor cortex returned to baseline, the faster the motor command in M1, and accordingly the shorter the RTs. Further, pairwise phase coherence between the motor areas showed that the more sustained the connection between the motor areas, the longer the RTs would be. The current findings illustrate the relationship between the temporal profiles of high-gamma power in human motor areas and response performance.

Laminar specificity and coverage of viral-mediated gene expression restricted to GABAergic interneurons and their parvalbumin subclass in marmoset primary visual cortex
In the mammalian neocortex, inhibition is important for dynamically balancing excitation and shaping the response properties of cells and circuits. The various functions of inhibition are thought to be mediated by different inhibitory neuron types of which a large diversity exists in several species. Current understanding of the function and connectivity of distinct inhibitory neuron types has mainly derived from studies in transgenic mice. However, it is unknown whether knowledge gained from mouse studies applies to the primate, the model system closest to humans. The lack of viral tools to selectively access inhibitory neuron types has been a major impediment to studying their function in the primate. Here, we have thoroughly validated and characterized several recently-developed viral vectors designed to restrict transgene expression to GABAergic cells or their parvalbumin (PV) subtype, and identified two types that show high specificity and efficiency in marmoset V1. We show that in marmoset V1 AAV-h56D induces transgene expression in GABAergic cells with up to 91-94% specificity and 80% efficiency, depending on viral serotype and cortical layer. AAV-PHP.eB-S5E2 induces transgene expression in PV cells across all cortical layers with up to 98% specificity and 86-90% efficiency. Thus, these viral vectors represent promising tools for studying GABA and PV cell function and connectivity in the primate cortex.

The neural dynamics of positive and negative expectations of pain
Pain is heavily modulated by expectations. Whereas the integration of expectations with sensory information has been examined in some detail, little is known about how positive and negative expectations are generated and their neural dynamics from generation over anticipation to the integration with sensory information. The present preregistered study employed a novel paradigm to induce positive and negative expectations on a trial-by-trial basis and examined the neural mechanisms using combined EEG-fMRI measurements (n=50). We observed substantially different neural representations between the anticipatory and the actual pain period. In the anticipation phase i.e., before the nociceptive input, the insular cortex, dorsolateral prefrontal cortex (DLPFC), and anterior cingulate cortex (ACC) showed increased activity for expectations regardless of their valence. Interestingly, a differentiation between positive and negative expectations within the majority of areas only occurred after the arrival of nociceptive information. FMRI-informed EEG analyses could reliably track the temporal sequence of processing showing an early effect in the DLPFC, followed by the anterior insula and late effects in the ACC. The observed effects indicate the involvement of different expectation-related subprocesses, including the transformation of visual information into a value signal that is maintained and differentiated according to its valence only during stimulus processing.

Understanding the complex interplay between tau, amyloid and the network in the spatiotemporal progression of Alzheimer's Disease
It is well known that A{beta} and tau proteins are deposited stereotypically in brain regions to cause Alzheimer's disease. The interaction of amyloid and tau in neurodegenerative diseases is a central feature and key to understanding AD pathophysiology. However their mechanisms are controversial, and many aspects do not fit current theories that rely on cell-autonomous factors. While cell culture and animal studies point to various interaction mechanisms between amyloid and tau, their causal direction and mode (local, remote or network-mediated) remain unknown in human subjects. Further, cross-protein interaction is yet to be reconciled with canonical observations that the two species do not co-localize significantly either in space or in time, and do not target the same neuronal populations. To answer these questions quantitatively, in this study we employed a mathematical reaction-diffusion model encoding the biophysical mechanisms underlying self-assembly, trans-neuronal network propagation and cross-species coupling of amyloid and tau. We first established that the spatiotemporal evolution of theoretical tau and A{beta} correctly predicts empirical patterns of regional A{beta}, tau and atrophy. Remarkably, the introduction of a 1-way A{beta}-->tau interaction was critical to the model's success. In comparison, both the non-interacting and the 2-way interaction models were significantly worse. We also found that network-mediated spread is essential; alternative modes of spread involving proximity or fiber length fare much worse. This mathematical exposition of the "pas de deux" of co-evolving proteins provides crucial quantitative and whole-brain support to the concept of amyloid-facilitated-tauopathy rather than the classic amyloid-cascade or pure-tau hypotheses, and helps explain certain known but poorly understood aspects of AD.

Optimal placement of high-channel visual prostheses in human retinotopic visual cortex
Recent strides in neurotechnology offer hope for restoring vision in individuals afflicted with blindness due to early visual pathway damage. We present a comprehensive method to optimize electrode placement for visual prostheses, with the objective of aligning with predetermined phosphene distributions. Our approach relies on individual anatomy data to minimize discrepancies between simulated and target phosphene patterns. While tailored for a 1000-channel 3D electrode array in V1, our algorithm is versatile, potentially accommodating any electrode design. Notably, our results show individually optimized placements outperform average brain solutions, underscoring the significance of anatomical specificity. Nevertheless, challenges persist in achieving comprehensive visual field coverage owing to current electrode constraints. We propose potential solutions involving multiple arrays to address this limitation. Additionally, considering intracranial vasculature constraints in future iterations could refine the optimization process. Our openly accessible software streamlines the refinement of surgical procedures and facilitates simulation studies, offering a realistic exploration of electrode design possibilities.

Circuits and mechanisms for TMS-induced corticospinal waves: Connecting sensitivityanalysis to the network graph
Transcranial magnetic stimulation (TMS) is a non-invasive, FDA-cleared treatment for neuropsychiatric disorders with broad potential for new applications, but the neural circuits that are engaged during TMS are still poorly understood. Recordings of neural activity from the corticospinal tract provide a direct readout of the response of motor cortex to TMS, and therefore a new opportunity to model neural circuit dynamics. The study goal was to use epidural recordings from the cervical spine of human subjects to develop a computational model of a motor cortical macrocolumn through which the mechanisms underlying the response to TMS, including direct and indirect waves, could be investigated. An in-depth sensitivity analysis was conducted to identify important pathways, and machine learning was used to identify common circuit features among these pathways. Sensitivity analysis identified neuron types that preferentially contributed to single corticospinal waves. Single wave preference could be predicted using the average connection probability of all possible paths between the activated neuron type and L5 pyramidal tract neurons (PTNs). For these activations, the total conduction delay of the shortest path to L5 PTNs determined the latency of the corticospinal wave. Finally, there were multiple neuron type activations that could preferentially modulate a particular corticospinal wave. The results support the hypothesis that different pathways of circuit activation contribute to different corticospinal waves with participation of both excitatory and inhibitory neurons. Moreover, activation of both afferents to the motor cortex as well as specific neuron types within the motor cortex initiated different I-waves, and the results were interpreted to propose the cortical origins of afferents that may give rise to certain I-waves. The methodology provides a workflow for performing computationally tractable sensitivity analyses on complex models and relating the results to the network structure to both identify and understand mechanisms underlying the response to acute stimulation.

Cell type-specific dynamics of prefrontal gamma synchrony during flexible behavior
The prefrontal cortex (PFC) is required for many cognitive processes that are disrupted in conditions such as schizophrenia. The PFC is composed of neuronal networks which are organized by both local microcircuitry and inter-regional projections, within which precisely tuned neuronal activity generates appropriate cognitive responses. Parvalbumin-positive interneurons (PVI) play an integral role by synchronizing select networks to oscillations in the gamma frequency range (~30-100 Hz). Synchronized gamma oscillations seem to facilitate information transfer between neurons and across regions. In particular, our lab has previously shown that PVI-generated gamma oscillations in the left and right prefrontal cortices become synchronized during cognitive tasks and this synchronization is necessary for animals to learn rule shifts. Here, we examine how this synchrony propagates through prefrontal circuits using novel genetically encoded voltage indicators (GEVIs) to examine gamma oscillations in specific populations of deep layer projection neurons targeting either the mediodorsal thalamus (PFC-MD) or dorsal striatum (PFC-DS). We first designed a novel analysis which found that PVI exhibit inter-hemispheric gamma synchrony immediately (within seconds) following trial outcomes, during a specific subset of trials associated with the adoption of a new behavioral strategy. PFC-MD neurons did not exhibit gamma synchrony during these outcome periods, but did synchronize during the pre-decision period of the next trial. Furthermore, pre-decision gamma synchrony in PFC-MD neurons was dependent on PVI and did not occur in PFC-DS neurons. Together, our findings suggest that gamma synchrony is transmitted from PVI to PFC-MD neurons during rule shifts in a task-phase and cell type-specific manner to facilitate the updating of behavioral strategies.

The functional anatomy of nociception: Effective Connectivity in Chronic Pain and Placebo Responders
There is growing recognition of cortical involvement in nociception. The present study is motivated by predictive coding formulations of pain perception that stress the importance of top-down and bottom-up information flow in the brain. It compares forward and backward effective connectivity - estimated from resting-state fMRI - between chronic osteoarthritic patients and healthy control subjects. Additionally, it assesses differences in effective connectivity between placebo responders and non-responders and asks whether these differences can be used to predict pain perception and placebo response. To assess hierarchical processing in nociception, we defined two primary cortical regions: primary somatosensory cortex (SSC) and posterior insula (PI) (primary interoceptive cortex) and lateral frontal pole (FP1), a terminal relay station of the pain processing pathways. The directed (effective) connectivity within and between these regions were estimated using spectral dynamic causal modeling (DCM). 56 osteoarthritis patients and 18 healthy controls were included in the analysis. Within the patient group, effective connectivity was compared between placebo responders and non-responders. In osteoarthritic patients, contra control group, forward connectivity from SSC to FP1 and from PI to FP1 was enhanced in the left hemisphere. Backward connections from FP1 to SSC were more inhibitory. Intrinsic (i.e., inhibitory recurrent or self-connectivity) of left FP1 increased. In placebo responders compared to non-responders, forward connections from bilateral SSC to PI, left SSC to FP1, left PI to left FP1 were more inhibitory. In addition, self-connections of bilateral PI and top-down connections from right FP1 to right SSC were disinhibited; whereas self-connections of right FP1 became increasingly inhibitory. We confirmed the robustness of these results in a leave-one-out cross-validation analysis of (out-of-sample) effect sizes. Overall, effective extrinsic and intrinsic effective connectivity among higher and lower cortical regions involved in pain processing emerges as a promising and quantifiable candidate marker of nociception and placebo response. The significance of these findings for clinical practice and neuroscience are discussed in relation to predictive processing accounts of placebo effects and chronic pain.