Biology subjects

Pack, C.

Publications and source records attributed to Pack, C..

8 recordsLinked to original sources

bioRxiv2026

TDP-43 amyloid conversion in cells tracks the net charge of a polyampholyte motif, not condensate solidification

Liquid-liquid phase separation of TDP-43 is implicated in ALS and FTLD, yet how its condensates convert into pathological amyloid in living cells remains poorly defined. Here we identify a polyampholyte motif (PAM) in the linker between RRM2 and the amyloid-forming low-complexity domain as a charge-tunable determinant of fibrillization that operates independently of condensate solidification. In budding yeast expressing GFP-TDP-43{Delta}NLS, charge reversal of three arginines (R268E/R272E/R275E; 3R-E) converted liquid puncta into ProteoStat-positive fibrils. Unexpectedly, fluorescence recovery after photobleaching showed 3R-E condensates to be more mobile than those of wild type, whereas the least mobile condensates, in yeast and in human U2OS cells, remained ProteoStat-negative. Across 24 PAM charge variants, the proportion of fibril-bearing cells scaled linearly with net charge regardless of residue identity, with charge neutralization delaying rather than abolishing conversion. Phosphomimetic substitution of the PAM serines alone induced fibrils, implicating phosphorylation as a potential physiological modulator of PAM charge.

biochemistry↗

bioRxiv2021

The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning

The visual system of mammals is comprised of parallel, hierarchical specialized pathways. Different pathways are specialized in so far as they use representations that are more suitable for supporting specific downstream behaviours. In particular, the clearest example is the specialization of the ventral ("what") and dorsal ("where") pathways of the visual cortex. These two pathways support behaviours related to visual recognition and movement, respectively. To-date, deep neural networks have mostly been used as models of the ventral, recognition pathway. However, it is unknown whether both pathways can be modelled with a single deep ANN. Here, we ask whether a single model with a single loss function can capture the properties of both the ventral and the dorsal pathways. We explore this question using data from mice, who like other mammals, have specialized pathways that appear to support recognition and movement behaviours. We show that when we train a deep neural network architecture with two parallel pathways using a self-supervised predictive loss function, we can outperform other models in fitting mouse visual cortex. Moreover, we can model both the dorsal and ventral pathways. These results demonstrate that a self-supervised predictive learning approach applied to parallel pathway architectures can account for some of the functional specialization seen in mammalian visual systems.

neuroscience↗

bioRxiv2020

Neural selectivity for visual motion in macaque area V3A

The processing of visual motion is carried out by dedicated pathways in the primate brain. These pathways originate with populations of direction-selective neurons in the primary visual cortex, which project to dorsal structures like the middle temporal (MT) and medial superior temporal (MST) areas. Anatomical and imaging studies have suggested that area V3A might also be specialized for motion processing, but there have been very few studies of single-neuron direction selectivity in this area. We have therefore performed electrophysiological recordings from V3A neurons in two macaque monkeys (one male and one female) and measured responses to a large battery of motion stimuli that includes translation motion, as well as more complex optic flow patterns. For comparison, we simultaneously recorded the responses of MT neurons to the same stimuli. Surprisingly, we find that overall levels of direction selectivity are similar in V3A and MT and moreover that the population of V3A neurons exhibits somewhat greater selectivity for optic flow patterns. These results suggest that V3A should be considered as part of the motion processing machinery of the visual cortex, in both human and non-human primates. Significance statementAlthough area V3A is frequently the target of anatomy and imaging studies, little is known about its functional role in processing visual stimuli. Its contribution to motion processing has been particularly unclear, with different studies yielding different conclusions. We report a detailed study of direction selectivity in V3A. Our results show that single V3A neurons are, on average, as capable of representing motion direction as are neurons in well-known structures like MT. Moreover, we identify a possible specialization for V3A neurons in representing complex optic flow, which has previously been thought to emerge in higher-order brain regions. Thus it appears that V3A is well-suited to a functional role in motion processing.

neuroscience↗

bioRxiv2020

Visual perceptual learning generalizes to untrained effectors

Visual perceptual learning (VPL) is an improvement in visual function following training. Although the practical utility of VPL was once thought to be limited by its specificity to the precise stimuli used during training, more recent work has shown that such specificity can be overcome with appropriate training protocols. In contrast, relatively little is known about the extent to which VPL exhibits motor specificity. Indeed, previous studies have shown that training paradigms that require one type of response (e.g., a button press) do not necessarily transfer to those that require a different response (e.g., a mouse movement). In this work, we have examined the effector specificity of VPL by training observers on tasks that maintain the same visual stimuli and task structure, but that require different effectors to indicate the response. We find that, in these conditions, VPL transfers fully between manual and oculomotor responses. These results are consistent with the idea that VPL entails the learning of a decision rule that can generalize across effectors.

neuroscience↗

bioRxiv2019

Influence of stimulus complexity on the specificity of visual perceptual learning

Although the structure and function of the human visual system are determined in large part during early development, there is ample evidence for adult plasticity as well. Such plasticity has important consequences for restoring vision after cortical damage and for improving function in healthy people. Although these applications have shown promising results, they are often limited by pathological specificity: Improvements obtained through perceptual training fail to generalize beyond the trained stimulus feature or location. Efforts to reduce specificity have focused on the design of training tasks, but less is known about the effects of stimulus structure on the specificity of perceptual learning. Here, we leverage physiological findings from the dorsal visual pathway of the primate brain to explore the hypothesis that learning specificity is related to the complexity of the training stimulus. Specifically, because neurons in higher-level structures of the dorsal visual pathway exhibit little stimulus specificity, we reasoned that training with more complex stimuli would reduce the specificity of learning. We trained human observers on stimuli of varying complexity, ranging from simple sinewave gratings to complex optic flow fields. Our results show that training with more complex stimuli reduces specificity for spatial position and stimulus features. Such changes are associated with increased spatial integration. These findings were captured by a computational \"reweighting\" model that decoded the outputs of simulated neurons in areas MT and MST of the primate visual cortex. Our results suggest that the addition of more complex stimuli into perceptual learning paradigms provides a simple and effective way to minimize specificity in learning.

neuroscience↗

bioRxiv2019

The Role of the Subthalamic Nucleus in Inhibitory Control of Oculomotor Behavior in Parkinson’s Disease

The ability to inhibit an inappropriate action in a context is an important part of the human cognitive repertoire, and deficiencies in this ability are common in neurological and psychiatric disorders. An anti-saccade is a simple experimental task within the oculomotor repertoire that can be used to test this ability. The task involves an inhibition of a saccade to the peripheral target (pro-saccade) and generation of a voluntary eye movement toward the mirror position (anti-saccade). Previous studies provide evidence for a possible contribution from the basal ganglia in anti-saccade behavior. However, the precise role of different components in generation of anti-saccade behavior is still uncertain. Parkinsons disease patients with implanted deep brain stimulation (DBS) in subthalamic nucleus (STN) provide us with a unique opportunity to investigate the role of STN in anti-saccade behavior. Previous attempts to show the effect of STN DBS on anti-saccades have produced conflicting observations. For example, the effect of STN DBS on anti-saccade error rate is not yet clear. Part of this inconsistency may be related to differences in dopaminergic states in different studies. Here, we tested Parkinsons disease patients on anti- and pro-saccade tasks ON and OFF STN DBS and ON and OFF dopaminergic medication. We made three main observations. First, STN DBS increases the anti-saccade error rate while patients are OFF dopamine replacement therapy. Second, there is an interaction between dopamine replacement therapy and STN DBS. More specifically, L-dopa reduces the effect of STN DBS on anti-saccade error rate. Third, STN DBS can induce different effects on pro- and anti-saccades in different patients. These observations provide evidence for an important role for the STN in the circuitry underlying context-dependent modulation of visuomotor action selection.

neuroscience↗

bioRxiv2019

Integrated Open-Source Software for Multiscale Electrophysiology

The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results.\n\nHere, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

neuroscience↗

bioRxiv2016

The contribution of area MT to visual motion perception depends on training

SummaryPerceptual decisions require the transformation of raw sensory inputs into cortical representations suitable for stimulus discrimination. One of the best-known examples of this transformation involves the middle temporal area (MT) of the primate visual cortex. Area MT provides a robust representation of stimulus motion, and previous work has shown that it contributes causally to performance on motion discrimination tasks. Here we report that the strength of this contribution can be highly plastic: Depending on the recent training history, pharmacological inactivation of MT can severely impair motion discrimination, or it can have little detectable influence. Similarly, depending on training, microstimulation can bias motion perception or simply introduce noise. Further analysis of neural and behavioral data suggests that training shifts the readout of motion information between MT and lower-level cortical areas. These results show that the contribution of individual brain regions to conscious perception can shift flexibly depending on sensory experience.

neuroscience↗