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A rapid whisker-based decision underlying skilled locomotion in mice.
Skilled motor behavior requires rapidly integrating external sensory input with information about internal state to decide which movements to make next. Using machine learning approaches for high-resolution kinematic analysis, we uncover the logic of a rapid decision underlying sensory-guided locomotion in mice. After detecting obstacles with their whiskers mice select distinct kinematic strategies depending on a whisker-derived estimate of obstacle location together with the position and velocity of their body. Although mice rely on whiskers for obstacle avoidance, lesions of primary whisker sensory cortex had minimal impact. While motor cortex manipulations affected the execution of the chosen strategy, the decision-making process remained largely intact. These results highlight the potential of machine learning for reductionist analysis of naturalistic behaviors and provide a case in which subcortical brain structures appear sufficient for mediating a relatively sophisticated sensorimotor decision.
Fast, volumetric imaging of in vivo mouse brain with swept confocally aligned planar excitation (SCAPE) microscopy
We demonstrate the use of SCAPE microscopy to image both neural activity via GCaMP and vascular hemodynamics in the awake behaving mouse brain at 10-20 volumes per second with cellular resolution over large fields of view. The performance of SCAPE is compared to in-vivo two-photon microscopy.
SCAPE microscopy for high-speed volumetric functional imaging of the awake, behaving brain
We present an improved SCAPE microscopy design that enhances system performance and ease of construction and can image many living samples including the awake, behaving mouse brain, zebrafish and Drosophila larva at >10 volumes/sec.
Brief Stimuli Cast a Persistent Long-Term Trace in Visual Cortex.
Visual processing is strongly influenced by recent stimulus history, a phenomenon termed adaptation. Prominent theories cast adaptation as a consequence of optimized encoding of visual information by exploiting the temporal statistics of the world. However, this would require the visual system to track the history of individual briefly experienced events, within a stream of visual input, to build up statistical representations over longer timescales. Here, using an openly available dataset from the Allen Brain Observatory, we show that neurons in the early visual cortex of the mouse indeed maintain long-term traces of individual past stimuli that persist despite the presentation of several intervening stimuli, leading to long-term and stimulus-specific adaptation over dozens of seconds. Long-term adaptation was selectively expressed in cortical, but not in thalamic, neurons, which only showed short-term adaptation. Early visual cortex thus maintains concurrent stimulus-specific memory traces of past input, enabling the visual system to build up a statistical representation of the world to optimize the encoding of new information in a changing environment.SIGNIFICANCE STATEMENT In the natural world, previous sensory input is predictive of current input over multisecond timescales. The visual system could exploit these predictabilities by adapting current visual processing to the long-term history of visual input. However, it is unclear whether the visual system can track the history of individual briefly experienced images, within a stream of input, to build up statistical representations over such long timescales. Here, we show that neurons in early visual cortex of the mouse brain exhibit remarkably long-term adaptation to brief stimuli, persisting over dozens of seconds, and despite the presentation of several intervening stimuli. The visual cortex thus maintains long-term traces of individual briefly experienced past images, enabling the formation of statistical representations over extended timescales.
Perceptual confirmation bias and decision bias underlie adaptation to sequential regularities.
Our perception does not depend exclusively on the immediate sensory input. It is also influenced by our internal predictions derived from prior observations and the temporal regularities of the environment, which can result in choice history biases. However, it is unclear how this flexible use of prior information to predict the future influences perceptual decisions. Prior information may bias decisions independently of the current sensory input, or it may modulate the weight of current sensory input based on its consistency with the expectation. To address this question, we used a visual decision-making task and manipulated the transitional probabilities between successive noisy grating stimuli. Using a reverse correlation analysis, we evaluated the contribution of stimulus-independent decision bias and stimulus-dependent sensitivity modulations to choice history biases. We found that both effects coexist, whereby there was increased bias to respond in line with the predicted orientation alongside modulations in perceptual sensitivity to favor perceptual information consistent with the prediction, akin to selective attention. Furthermore, at the individual differences level, we investigated the relationship between autistic-like traits and the adaptation of choice history biases to the sequential statistics of the environment. Over two studies, we found no convincing evidence of reduced adaptation to sequential regularities in individuals with high autistic-like traits. In sum, we present robust evidence for both perceptual confirmation bias and decision bias supporting adaptation to sequential regularities in the environment.
Subcortical origin of nonlinear sound encoding in auditory cortex.
A major challenge in neuroscience is to understand how neural representations of sensory information are transformed by the network of ascending and descending connections in each sensory system. By recording from neurons at several levels of the auditory pathway, we show that much of the nonlinear encoding of complex sounds in auditory cortex can be explained by transformations in the midbrain and thalamus. Modeling cortical neurons in terms of their inputs across these subcortical populations enables their responses to be predicted with unprecedented accuracy. By contrast, subcortical responses cannot be predicted from descending cortical inputs, indicating that ascending transformations are irreversible, resulting in increasingly lossy, higher-order representations across the auditory pathway. Rather, auditory cortex selectively modulates the nonlinear aspects of thalamic auditory responses and the functional coupling between subcortical neurons without affecting the linear encoding of sound. These findings reveal the fundamental role of subcortical transformations in shaping cortical responses.
How and why eLife selects papers for peer review
When deciding which submissions should be peer reviewed, eLife editors consider whether they will be able to find high-quality reviewers, and whether the reviews will be valuable to the scientific community.
Relevance of genetic testing in the gene-targeted trial era: the Rostock Parkinson's disease study.
Estimates of the spectrum and frequency of pathogenic variants in Parkinson's disease (PD) in different populations are currently limited and biased. Furthermore, although therapeutic modification of several genetic targets has reached the clinical trial stage, a major obstacle in conducting these trials is that PD patients are largely unaware of their genetic status and, therefore, cannot be recruited. Expanding the number of investigated PD-related genes and including genes related to disorders with overlapping clinical features in large, well-phenotyped PD patient groups is a prerequisite for capturing the full variant spectrum underlying PD and for stratifying and prioritizing patients for gene-targeted clinical trials. The Rostock Parkinson's disease (ROPAD) study is an observational clinical study aiming to determine the frequency and spectrum of genetic variants contributing to PD in a large international cohort. We investigated variants in 50 genes with either an established relevance for PD or possible phenotypic overlap in a group of 12 580 PD patients from 16 countries [62.3% male; 92.0% White; 27.0% positive family history (FH+), median age at onset (AAO) 59 years] using a next-generation sequencing panel. Altogether, in 1864 (14.8%) ROPAD participants (58.1% male; 91.0% White, 35.5% FH+, median AAO 55 years), a PD-relevant genetic test (PDGT) was positive based on GBA1 risk variants (10.4%) or pathogenic/likely pathogenic variants in LRRK2 (2.9%), PRKN (0.9%), SNCA (0.2%) or PINK1 (0.1%) or a combination of two genetic findings in two genes (∼0.2%). Of note, the adjusted positive PDGT fraction, i.e. the fraction of positive PDGTs per country weighted by the fraction of the population of the world that they represent, was 14.5%. Positive PDGTs were identified in 19.9% of patients with an AAO ≤ 50 years, in 19.5% of patients with FH+ and in 26.9% with an AAO ≤ 50 years and FH+. In comparison to the idiopathic PD group (6846 patients with benign variants), the positive PDGT group had a significantly lower AAO (4 years, P = 9 × 10-34). The probability of a positive PDGT decreased by 3% with every additional AAO year (P = 1 × 10-35). Female patients were 22% more likely to have a positive PDGT (P = 3 × 10-4), and for individuals with FH+ this likelihood was 55% higher (P = 1 × 10-14). About 0.8% of the ROPAD participants had positive genetic testing findings in parkinsonism-, dystonia/dyskinesia- or dementia-related genes. In the emerging era of gene-targeted PD clinical trials, our finding that ∼15% of patients harbour potentially actionable genetic variants offers an important prospect to affected individuals and their families and underlines the need for genetic testing in PD patients. Thus, the insights from the ROPAD study allow for data-driven, differential genetic counselling across the spectrum of different AAOs and family histories and promote a possible policy change in the application of genetic testing as a routine part of patient evaluation and care in PD.
The relationship between visual acuity loss and GABAergic inhibition in amblyopia
Abstract Early childhood experience alters visual development, a process exemplified by amblyopia, a common neurodevelopmental condition resulting in cortically reduced vision in one eye. Visual deficits in amblyopia may be a consequence of abnormal suppressive interactions in the primary visual cortex by inhibitory neurotransmitter γ-aminobutyric acid (GABA). We examined the relationship between visual acuity loss and GABA+ in adult human participants with amblyopia. Single voxel proton magnetic resonance spectroscopy (MRS) data were collected from the early visual cortex (EVC) and posterior cingulate cortex (control region) of twenty-eight male and female adults with current or past amblyopia while they viewed flashing checkerboards monocularly, binocularly, or while they had their eyes closed. First, we compared GABA+ concentrations between conditions to evaluate suppressive binocular interactions. Then, we correlated the degree of visual acuity loss with GABA+ levels to test whether GABAergic inhibition could explain visual acuity deficits. Visual cortex GABA+ was not modulated by viewing condition, and we found weak evidence for a negative correlation between visual acuity deficits and GABA+. These findings suggest that reduced vision in one eye due to amblyopia is not strongly linked to GABAergic inhibition in the visual cortex. We advanced our understanding of early experience dependent plasticity in the human brain by testing the association between visual acuity deficits and visual cortex GABA in amblyopes of the most common subtypes. Our study shows that the relationship was not as clear as expected and provides avenues for future investigation.
Extraordinary model systems for regeneration
ABSTRACT Regeneration is the remarkable phenomenon through which an organism can regrow lost or damaged parts with fully functional replacements, including complex anatomical structures, such as limbs. In 2019, Development launched its ‘Model systems for regeneration’ collection, a series of articles introducing some of the most popular model organisms for studying regeneration in vivo. To expand this topic further, this Perspective conveys the voices of five expert biologists from the field of regenerative biology, each of whom showcases some less well-known, but equally extraordinary, species for studying regeneration.
The Oxford Encyclopedia of Sensory Systems
61 articles The Oxford Encyclopedia of Sensory Systems brings together a comprehensive account of the diversity of mechanisms that organisms use to sense the natural world. Organized into topical sections, with chapters written by more than 100 leading experts in the field of sensory neuroscience, the Encyclopedia presents foundational and emerging topics, all with an eye toward suggesting directions for future research.
Protocol for separating cancer cell subpopulations by metabolic activity using flow cytometry.
Cells, even from the same line, can maintain heterogeneity in metabolic activity. Here, we present a protocol, adapted for fluorescence-activated cell sorting (FACS), that separates resuspended cells according to their metabolic rate. We describe steps for driving lactate efflux, which produces an alkaline transient proportional to fermentative rate. This pH signature, measured using pH-sensitive dyes, identifies cells with the highest metabolic rate. We then describe a fluorimetric assay of oxygen consumption and acid production to confirm the metabolic contrast between subpopulations. For complete details on the use and execution of this protocol, please refer to Blaszczak et al.1.