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Hierarchical temporal prediction captures motion processing from retina to higher visual cortex
Visual neurons respond selectively to specific features that become increasingly complex in their form and dynamics from the eyes to the cortex. Retinal neurons prefer localized flashing spots of light, primary visual cortical (V1) neurons moving bars, and those in higher cortical areas, such as middle temporal (MT) cortex, favor complex features like moving textures. Whether there are general computational principles behind this diversity of response properties remains unclear. To date, no single normative model has been able to account for the hierarchy of tuning to dynamic inputs along the visual pathway. Here we show that hierarchical application of temporal prediction - representing features that efficiently predict future sensory input from past sensory input - can explain how neuronal tuning properties, particularly those relating to motion, change from retina to higher visual cortex. This suggests that the brain may not have evolved to efficiently represent all incoming information, as implied by some leading theories. Instead, the selective representation of sensory inputs that help in predicting the future may be a general neural coding principle, which when applied hierarchically extracts temporally-structured features that depend on increasingly high-level statistics of the sensory input.
Simple spectral transformations capture the contribution of peripheral processing to cortical responses to natural sounds
Processing in the sensory periphery involves various mechanisms that enable the detection and discrimination of sensory information. Despite their biological complexity, could these processing steps sub-serve a relatively simple transformation of sensory inputs, which are then transmitted to the CNS? Here we explored both biologically-detailed and very simple models of the auditory periphery to find the appropriate input to a phenomenological model of auditory cortical responses to natural sounds. We examined a range of cochlear models, from those involving detailed biophysical characteristics of the cochlea and auditory nerve to very pared-down spectrogram-like approximations of the information processing in these structures. We tested the capacity of these models to predict the time-course of single-unit neural responses recorded in the ferret primary auditory cortex, when combined with a linear non-linear encoding model. We show that a simple model based on a log-spaced, log-scaled power spectrogram with Hill-function compression performs as well as biophysically-detailed models of the cochlea and the auditory nerve. These findings emphasize the value of using appropriate simple models of the periphery when building encoding models of sensory processing in the brain, and imply that the complex properties of the auditory periphery may together result in a simpler than expected functional transformation of the inputs.
Simple spectral transformations capture the contribution of peripheral processing to cortical responses to natural sounds
Processing in the sensory periphery involves various mechanisms that enable the detection and discrimination of sensory information. Despite their biological complexity, could these processing steps sub-serve a relatively simple transformation of sensory inputs, which are then transmitted to the CNS? Here we explored both biologically-detailed and very simple models of the auditory periphery to find the appropriate input to a phenomenological model of auditory cortical responses to natural sounds. We examined a range of cochlear models, from those involving detailed biophysical characteristics of the cochlea and auditory nerve to very pared-down spectrogram-like approximations of the information processing in these structures. We tested the capacity of these models to predict the time-course of single-unit neural responses recorded in the ferret primary auditory cortex, when combined with a linear non-linear encoding model. We show that a simple model based on a log-spaced, log-scaled power spectrogram with Hill-function compression performs as well as biophysically-detailed models of the cochlea and the auditory nerve. These findings emphasize the value of using appropriate simple models of the periphery when building encoding models of sensory processing in the brain, and imply that the complex properties of the auditory periphery may together result in a simpler than expected functional transformation of the inputs.
Pitch discrimination performance of ferrets and humans on a go/no-go task
ABSTRACTAnimal models are widely used to examine the neurophysiological basis of human pitch perception, and it is therefore important to understand the similarities and differences in pitch processing across species. Pitch discrimination performance is usually measured using two-alternative forced choice (2AFC) procedures in humans and go/no-go tasks in animals, potentially confounding human-to-animal comparisons. We have previously shown that pitch discrimination thresholds of ferrets on a 2AFC task are markedly poorer than those reported for go/no-go tasks in other non-human species (Walker et al., 2009). To better compare the pitch discrimination performance of ferret with other species, here we measure pitch change detection thresholds of ferrets and humans on a common, appetitive go/no-go task design. We found that ferrets’ pitch thresholds were ~10 times larger than that of humans on the go/no-go task, and were within the range of thresholds reported in other non-human species. Interestingly, ferrets’ thresholds were 100 times larger than human thresholds on a 2AFC pitch discrimination task using the same stimuli. These results emphasize that sensory discrimination thresholds can differ across tasks, particularly for non-human animals. Performance on our go/no-go task is likely to reflect different neurobiological processes than that on our 2AFC task, as the former required the subjects only to detect a pitch change while the latter required them to label the direction of the pitch change.ABBREVIATIONS2AFC2-Alternative Forced ChoiceF0Fundamental FrequencyHIGHLIGHTSPitch discrimination thresholds of ferrets were 10 times larger than those of humans on a go/no-go taskFerrets’ pitch thresholds are similar to those reported for a range of other mammalsPitch thresholds of ferrets, but not humans, were drastically better on the go/no-go task than a 2AFC task using the same stimuli
Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.
OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024.
Noise suppression of proton magnetic resonance spectroscopy improves paediatric brain tumour classification.
Proton magnetic resonance spectroscopy (1 H-MRS) is increasingly used for clinical brain tumour diagnosis, but suffers from limited spectral quality. This retrospective and comparative study aims at improving paediatric brain tumour classification by performing noise suppression on clinical 1 H-MRS. Eighty-three/forty-two children with either an ependymoma (ages 4.6 ± $$ \pm $$ 5.3/9.3 ± $$ \pm $$ 5.4), a medulloblastoma (ages 6.9 ± $$ \pm $$ 3.5/6.5 ± $$ \pm $$ 4.4), or a pilocytic astrocytoma (8.0 ± $$ \pm $$ 3.6/6.3 ± $$ \pm $$ 5.0), recruited from four centres across England, were scanned with 1.5T/3T short-echo-time point-resolved spectroscopy. The acquired raw 1 H-MRS was quantified by using Totally Automatic Robust Quantitation in NMR (TARQUIN), assessed by experienced spectroscopists, and processed with adaptive wavelet noise suppression (AWNS). Metabolite concentrations were extracted as features, selected based on multiclass receiver operating characteristics, and finally used for identifying brain tumour types with supervised machine learning. The minority class was oversampled through the synthetic minority oversampling technique for comparison purposes. Post-noise-suppression 1 H-MRS showed significantly elevated signal-to-noise ratios (P < .05, Wilcoxon signed-rank test), stable full width at half-maximum (P > .05, Wilcoxon signed-rank test), and significantly higher classification accuracy (P < .05, Wilcoxon signed-rank test). Specifically, the cross-validated overall and balanced classification accuracies can be improved from 81% to 88% overall and 76% to 86% balanced for the 1.5T cohort, whilst for the 3T cohort they can be improved from 62% to 76% overall and 46% to 56%, by applying Naïve Bayes on the oversampled 1 H-MRS. The study shows that fitting-based signal-to-noise ratios of clinical 1 H-MRS can be significantly improved by using AWNS with insignificantly altered line width, and the post-noise-suppression 1 H-MRS may have better diagnostic performance for paediatric brain tumours.
Oncogenic cell tagging and single-cell transcriptomics reveal cell type-specific and time-resolved responses to Vhl inactivation in the kidney.
Defining the initial events in oncogenesis and the cellular responses they entrain, even in advance of morphological abnormality, is a fundamental challenge in understanding cancer initiation. As a paradigm to address this, we longitudinally studied the changes induced by loss of the tumor suppressor gene von Hippel Lindau (VHL), which ultimately drives clear cell renal cell carcinoma. Vhl inactivation was directly coupled to expression of a tdTomato reporter within a single allele, allowing accurate visualization of affected cells in their native context and retrieval from the kidney for single-cell RNA-sequencing. This strategy uncovered cell-type specific responses to Vhl inactivation, defined a proximal tubular cell class with oncogenic potential, and revealed longer term adaptive changes in the renal epithelium and the interstitium. Oncogenic cell tagging also revealed markedly heterogeneous cellular effects including time-limited proliferation and elimination of specific cell types. Overall, this study reports an experimental strategy for understanding oncogenic processes in which cells bearing genetic alterations can be generated in their native context, marked, and analyzed over time. The observed effects of loss of Vhl in kidney cells provide insights into VHL tumor suppressor action and development of renal cell carcinoma.
Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches.
Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.
Frequency and outcomes of gastrostomy insertion in a longitudinal cohort study of atypical parkinsonism.
BACKGROUND: Multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) show a high prevalence and rapid progression of dysphagia, which is associated with reduced survival. Despite this, the evidence base for gastrostomy is poor, and the optimal frequency and outcomes of this intervention are not known. We aimed to characterise the prevalence and outcomes of gastrostomy in patients with these three atypical parkinsonian disorders. METHOD: We analysed data from the natural history and longitudinal cohorts of the PROSPECT-M-UK study with up to 60 months of follow-up from baseline. Survival post-gastrostomy was analysed using Kaplan-Meier survival curves. RESULTS: In a total of 339 patients (mean age at symptom onset 63.3 years, mean symptom duration at baseline 4.6 years), dysphagia was present in >50% across all disease groups at baseline and showed rapid progression during follow-up. Gastrostomy was recorded as recommended in 44 (13%) and performed in 21 (6.2%; MSA 7, PSP 11, CBS 3) of the total study population. Median survival post-gastrostomy was 24 months compared with 12 months where gastrostomy was recommended but not done (p = 0.008). However, this was not significant when correcting for age and duration of symptoms at the time of procedure or recommendation. CONCLUSIONS: Gastrostomy was performed relatively infrequently in this cohort despite the high prevalence of dysphagia. Survival post-gastrostomy was longer than previously reported, but further data on other outcomes and clinician and patient perspectives would help to guide use of this intervention in MSA, PSP and CBS.
Effects of clozapine-N-oxide and compound 21 on sleep in laboratory mice.
Designer receptors exclusively activated by designer drugs (DREADDs) are chemogenetic tools for remote control of targeted cell populations using chemical actuators that bind to modified receptors. Despite the popularity of DREADDs in neuroscience and sleep research, potential effects of the DREADD actuator clozapine-N-oxide (CNO) on sleep have never been systematically tested. Here, we show that intraperitoneal injections of commonly used CNO doses (1, 5, and 10 mg/kg) alter sleep in wild-type male laboratory mice. Using electroencephalography (EEG) and electromyography (EMG) to analyse sleep, we found a dose-dependent suppression of rapid eye movement (REM) sleep, changes in EEG spectral power during non-REM (NREM) sleep, and altered sleep architecture in a pattern previously reported for clozapine. Effects of CNO on sleep could arise from back-metabolism to clozapine or binding to endogenous neurotransmitter receptors. Interestingly, we found that the novel DREADD actuator, compound 21 (C21, 3 mg/kg), similarly modulates sleep despite a lack of back-metabolism to clozapine. Our results demonstrate that both CNO and C21 can modulate sleep of mice not expressing DREADD receptors. This implies that back-metabolism to clozapine is not the sole mechanism underlying side effects of chemogenetic actuators. Therefore, any chemogenetic experiment should include a DREADD-free control group injected with the same CNO, C21, or newly developed actuator. We suggest that electrophysiological sleep assessment could serve as a sensitive tool to test the biological inertness of novel chemogenetic actuators.
Neuronal and astrocyte determinants of critical periods of plasticity.
Windows of plasticity allow environmental experiences to produce intense activity-dependent changes during postnatal development. The reordering and refinement of neural connections occurs during these periods, significantly influencing the formation of brain circuits and physiological processes in adults. Recent advances have shed light on factors that determine the onset and duration of sensitive and critical periods of plasticity. Although GABAergic inhibition has classically been implicated in closing windows of plasticity, astrocytes and adenosinergic inhibition have also emerged more recently as key determinants of the duration of these periods of plasticity. Here, we review novel aspects of the involvement of GABAergic inhibition, the possible role of presynaptic NMDARs, and the emerging roles of astrocytes and adenosinergic inhibition in determining the duration of windows of plasticity in different brain regions.
NMDA Receptors Containing GluN2B/2C/2D Subunits Mediate an Increase in Glutamate Release at Hippocampal CA3-CA1 Synapses.
NMDA receptors (NMDARs) are involved in synaptic transmission and synaptic plasticity in different brain regions, and they modulate glutamate release at different presynaptic sites. Here, we studied whether non-postsynaptic NMDARs, putatively presynaptic (preNMDARs), are tonically active at hippocampal CA3-CA1 synapses, and if they modulate glutamate release. We found that when postsynaptic NMDARs are blocked by MK801, D-AP5 depresses evoked and spontaneous excitatory synaptic transmission, indicating that preNMDARs are tonically active at CA3-CA1 synapses, facilitating glutamate release. The subunit composition of these NMDARs was determined by studying evoked and spontaneous excitatory synaptic transmission in the presence of Zn2+, Ro 25-6981, and PPDA, antagonists of NMDARs containing GluN2A, GluN2B, and GluN2C/D, respectively. We found that evoked and spontaneous release decreased when the activity of NMDARs containing GluN2B and GluN2C/D subunits but not GluN2A was impeded. In addition, we found that the increase in glutamate release mediated by these NMDARs requires protein kinase A (PKA) activation. We conclude that preNMDARs that contain GluN2B and GluN2C/2D subunits facilitate glutamate release at hippocampal CA3-CA1 synapses through a mechanism that involves PKA.
Adenosine Receptor-Mediated Developmental Loss of Spike Timing-Dependent Depression in the Hippocampus.
Critical periods of synaptic plasticity facilitate the reordering and refining of neural connections during development, allowing the definitive synaptic circuits responsible for correct adult physiology to be established. Presynaptic spike timing-dependent long-term depression (t-LTD) exists in the hippocampus, which depends on the activation of NMDARs and that probably fulfills a role in synaptic refinement. This t-LTD is present until the third postnatal week in mice, disappearing in the fourth week of postnatal development. We were interested in the mechanisms underlying this maturation related loss of t-LTD and we found that at CA3-CA1 synapses, presynaptic NMDA receptors (pre-NMDARs) are tonically active between P13 and P21, mediating an increase in glutamate release during this critical period of plasticity. Conversely, at the end of this critical period (P22-P30) and coinciding with the loss of t-LTD, these pre-NMDARs are no longer tonically active. Using immunogold electron microscopy, we demonstrated the existence of pre-NMDARs at Schaffer collateral synaptic boutons, where a decrease in the number of pre-NMDARs during development coincides with the loss of both tonic pre-NMDAR activation and t-LTD. Interestingly, this t-LTD can be completely recovered by antagonizing adenosine type 1 receptors (A1R), which also recovers the tonic activation of pre-NMDARs at P22-P30. By contrast, the induction of t-LTD was prevented at P13-P21 by an agonist of A1R, as was tonic pre-NMDAR activation. Furthermore, we found that the adenosine that mediated the loss of t-LTD during the fourth week of development is supplied by astrocytes. These results provide direct evidence for the mechanism that closes the window of plasticity associated with t-LTD, revealing novel events probably involved in synaptic remodeling during development.
Astrocyte-mediated switch in spike timing-dependent plasticity during hippocampal development.
Presynaptic spike timing-dependent long-term depression (t-LTD) at hippocampal CA3-CA1 synapses is evident until the 3rd postnatal week in mice, disappearing during the 4th week. At more mature stages, we found that the protocol that induced t-LTD induced t-LTP. We characterized this form of t-LTP and the mechanisms involved in its induction, as well as that driving this switch from t-LTD to t-LTP. We found that this t-LTP is expressed presynaptically at CA3-CA1 synapses, as witnessed by coefficient of variation, number of failures, paired-pulse ratio and miniature responses analysis. Additionally, this form of presynaptic t-LTP does not require NMDARs but the activation of mGluRs and the entry of Ca2+ into the postsynaptic neuron through L-type voltage-dependent Ca2+ channels and the release of Ca2+ from intracellular stores. Nitric oxide is also required as a messenger from the postsynaptic neuron. Crucially, the release of adenosine and glutamate by astrocytes is required for t-LTP induction and for the switch from t-LTD to t-LTP. Thus, we have discovered a developmental switch of synaptic transmission from t-LTD to t-LTP at hippocampal CA3-CA1 synapses in which astrocytes play a central role and revealed a form of presynaptic LTP and the rules for its induction.
The hypothalamic link between arousal and sleep homeostasis in mice.
Sleep and wakefulness are not simple, homogenous all-or-none states but represent a spectrum of substates, distinguished by behavior, levels of arousal, and brain activity at the local and global levels. Until now, the role of the hypothalamic circuitry in sleep-wake control was studied primarily with respect to its contribution to rapid state transitions. In contrast, whether the hypothalamus modulates within-state dynamics (state "quality") and the functional significance thereof remains unexplored. Here, we show that photoactivation of inhibitory neurons in the lateral preoptic area (LPO) of the hypothalamus of adult male and female laboratory mice does not merely trigger awakening from sleep, but the resulting awake state is also characterized by an activated electroencephalogram (EEG) pattern, suggesting increased levels of arousal. This was associated with a faster build-up of sleep pressure, as reflected in higher EEG slow-wave activity (SWA) during subsequent sleep. In contrast, photoinhibition of inhibitory LPO neurons did not result in changes in vigilance states but was associated with persistently increased EEG SWA during spontaneous sleep. These findings suggest a role of the LPO in regulating arousal levels, which we propose as a key variable shaping the daily architecture of sleep-wake states.