Biology subjects

Scherberger, H.

Publications and source records attributed to Scherberger, H..

6 recordsLinked to original sources

bioRxiv2023

Accurate neuroprosthetic control through latent state transition training

Brain-computer interfaces (BCIs) have the potential to restore hand movement for people with paralysis, but current devices still lack the fine control required to interact with objects of daily living. Following understanding of cortical activity during arm reaches, hand BCI studies have focused on velocity control. However, mounting evidence suggests that posture, and not velocity, dominates in hand-related areas during natural movement. To explore whether this signal can causally control a prosthesis, we developed a novel BCI training paradigm centered on the reproduction of hand posture transitions. Macaque monkeys trained with the protocol were able to control a multi-dimensional hand prosthesis at high-accuracy, including execution of the very intricate precision grip. Subsequent analysis revealed that the posture signal in the target grasping areas was a major contributor to control. Population activity exhibited pattern separation and dimensionality increases driven by posture kinematics, and simulations with a grasping circuit model demonstrated the generalizability of our approach. We present for the first time neural posture control of a multi-dimensional hand prosthesis, opening the door for future devices to leverage this additional information channel.

neuroscience↗

bioRxiv2022

Overcoming the Reproducibility Crisis - Results of the first Community Survey of the German National Research Data Infrastructure for Neuroscience.

The lack of reproducibility of research results is a serious problem - known as "the reproducibility crisis". The German National Research Data Infrastructure (NFDI) initiative implemented by the German Research Foundation (DFG) aims to help overcoming this crisis by developing sustainable solutions for research data management (RDM). NFDI comprises domain specific consortia across all science disciplines. In the field of neuroscience, NFDI Neuroscience (NFDI-Neuro) contributes to the strengthening of systematic and standardized RDM in its research communities. NFDI-Neuro conducted a comprehensive survey amongst the neuroscience community to determine the current needs, challenges, and opinions with respect to RDM. The outcomes of this survey are presented here. The German neuroscience community perceives barriers with respect to RDM and data sharing mainly linked to (1) lack of data and metadata standards, (2) lack of community adopted provenance tracking methods, 3) lack of a privacy preserving research infrastructure for sensitive data (4) lack of RDM literacy and (5) lack of required time and resources for proper RDM. NFDI-Neuro aims to systematically address these barriers by leading and contributing to the development of standards, tools, and infrastructure and by providing training, education, and support, as well as additional resources for RDM to its research community. The RDM work of NFDI-Neuro is conducted in close collaboration with its partner EBRAINS AISBL, the coordinating entity of the EU Flagship Human Brain Project, and its Research Infrastructure (RI) EBRAINS with more than 5000 registered users and developers from more than 70 countries of all continents. While NFDI-Neuro aims to address the German national needs, it closely aligns with the international community and the topics of the Digital Europe Program and EU Data Spaces. Significance StatementA comprehensive survey amongst the neuroscience community in Germany determined the current needs, challenges, and opinions with respect to standardized research data management (RDM) to overcome the reproducibility crisis. Significant deficits were pointed out concerning the perceived lack of standards for data and metadata, lack of provenance tracking and versioning of data, lack of protected digital research infrastructure for sensitive data and the lack of education and resources for proper RDM. Yet, at the same time, an overwhelming majority of community members indicated that they would be willing to share their data with other researchers and are interested to increase their RDM skills. Thus, the survey results suggest that training, the provision of standards, tools, infrastructure and additional resources for RDM holds the potential to significantly facilitate reproducible research in neuroscience.

neuroscience↗

bioRxiv2021

Information dynamics in neuronal networks of macaque cerebral cortex reflect cognitive state and behavior.

One of the essential functions biological neural networks is the processing of information. This comprises processing sensory information to perceive the environment, up to processing motor information to interact with the environment. Due to methodological concerns, it has been historically unclear how information processing changes during different cognitive or behavioral states, and to what extent information is processed within or between the network of neurons in different brain areas. In this study, we leverage recent advances in the calculation of information dynamics to explore neural-level processing within and between the fronto-parietal areas AIP, F5 and M1 during a delayed grasping task performed by three macaque monkeys. While information processing was high within all areas during all cognitive and behavioral states of the task, inter-areal processing varied widely: during visuo-motor transformation, AIP and F5 formed a reciprocally connected processing unit, while no processing was present between areas during the memory period. Movement execution was processed globally across all areas with a predominance of processing in the feedback direction. Additionally, the fine-scale network structure re-configured at the neuron-level in response to different grasping conditions, despite of no differences in the overall amount of information present. These results suggest that areas dynamically form higher-order processing units according to the cognitive or behavioral demand, and that the information processing network is hierarchically organized at the neuron-level, with the coarse network structure determining the behavioral state and finer changes reflecting different conditions. Significance StatementWhat does it mean to say that the brain "processes information?" Scientists often discuss the brain in terms of information processing - animals take in information from their environment through their senses, and use it to make decisions about how to act in the world. In this work, we use a mathematical framework called information theory to explore how signals from the environment influence brain activity, and how brain activity in turn informs on behaviors. We found that different brain regions processed information in dynamic and flexible ways, with signals flowing up and down the hierarchy of sensory-motor depending on the demands of the moment. This shows how "computation" in the brain can reflect complex behaviors and cognitive states.

neuroscience↗

bioRxiv2019

A neural network model of flexible grasp movement generation

One of the primary ways we interact with the world is using our hands. In macaques, the circuit spanning the anterior intraparietal area, the hand area of the ventral premotor cortex, and the primary motor cortex is necessary for transforming visual information into grasping movements. We hypothesized that a recurrent neural network mimicking the multi-area structure of the anatomical circuit and using visual features to generate the required muscle dynamics to grasp objects would explain the neural and computational basis of the grasping circuit. Modular networks with object feature input and sparse inter-module connectivity outperformed other models at explaining neural data and the inter-area relationships present in the biological circuit, despite the absence of neural data during network training. Network dynamics were governed by simple rules, and targeted lesioning of modules produced deficits similar to those observed in lesion studies, providing a potential explanation for how grasping movements are generated.

neuroscience↗

bioRxiv2017

Neural dynamics of variable grasp movement preparation in the macaque fronto-parietal network

Our voluntary grasping actions lie on a continuum between immediate action and waiting for the right moment, depending on the context. Therefore, studying grasping requires investigating how preparation time affects this process. Two macaque monkeys (Macaca mulatta) performed a grasping task with a short instruction followed by an immediate or delayed go cue (0-1300 ms) while we recorded in parallel from neurons in the hand area (F5) of the ventral premotor cortex and the anterior intraparietal area (AIP). Initial population dynamics followed a fixed trajectory in the neural state space unique to each grip type, reflecting unavoidable preparation, then diverged depending on the delay. Although similar types of single unit responses were present in both areas, population activity in AIP stabilized within a unique memory state while F5 activity continued to evolve, tracking subjective anticipation of the go cue. Intriguingly, activity during movement initiation clustered into two trajectory clusters, corresponding to movements that were either as fast as possible or withheld movements, demonstrating a widespread state shift in the fronto-parietal grasping network when movements must be withheld. Our results reveal how dissociation between static and dynamic components of movement preparation as well as differentiation between cortical areas is possible through population level analysis.\n\nSignificance StatementMany of our movements must occur with no warning, while others we can prepare in advance. Yet, its unclear how planning for movements along the spectrum between these two situations differs in the brain. Two macaque monkeys made reach to grasp movements after varying amounts of preparation time while we recorded from premotor and parietal cortex. We found that the initial response to a grasp instruction was specific to the required movement, but not the preparation time, reflecting required processing. However, when more preparation time was given, neural activity achieved unique states that likely related to withholding movements and anticipation of movement, which was more prevalent in premotor cortex, suggesting differing roles of premotor and parietal cortex in grasp planning.

neuroscience↗

bioRxiv2017

Population coding of grasp and laterality-related information in the macaque fronto-parietal network

Preparing and executing grasping movements demands the coordination of sensory information across multiple scales. The position of an object, required hand shape, and which of our hands to extend must all be coordinated in parallel. The network formed by the macaque anterior intraparietal area (AIP) and hand area (F5) of the ventral premotor cortex is essential in the generation of grasping movements. Yet, the role of this circuit in hand selection is unclear. We recorded from 1342 single- and multi-units in AIP and F5 of two macaque monkeys (Macaca mulatta) during a delayed grasping task in which monkeys were instructed by a visual cue to perform power or precision grips on a handle presented in five different orientations with either the left or right hand, as instructed by an auditory tone. In AIP, intended hand use was only weakly represented during preparation, while hand use was robustly present in F5 during preparation. Interestingly, visual-centric handle orientation information dominated AIP, while F5 contained an additional body-centric frame during preparation and movement. Together, our results implicate F5 as a site of visuo-motor transformation and advocate a strong transition between hand-invariant and hand-specific representations in this parieto-frontal circuit.

neuroscience↗