Scherberger, Hansjörg

[["dc.contributor.author","Andersen, Richard A."],["dc.contributor.author","Burdick, J. W."],["dc.contributor.author","Musallam, S."],["dc.contributor.author","Scherberger, Hansjörg"],["dc.contributor.author","Pesaran, B."],["dc.contributor.author","Meeker, D."],["dc.contributor.author","Corneil, B. D."],["dc.contributor.author","Fineman, I."],["dc.contributor.author","Nenadic, Z."],["dc.contributor.author","Branchaud, E."],["dc.contributor.author","Cham, J. G."],["dc.contributor.author","Greger, B."],["dc.contributor.author","Tai, Y. C."],["dc.contributor.author","Mojarradi, M. M."],["dc.date.accessioned","2017-09-07T11:53:55Z"],["dc.date.available","2017-09-07T11:53:55Z"],["dc.date.issued","2005"],["dc.description.abstract","An important challenge for neural prosthetics research is to record from populations of neurons over long periods of time, ideally for the lifetime of the patient. Two new advances toward this goal are described, the use of local field potentials (LFPs) and autonomously positioned recording electrodes. LFPs are the composite extracellular potential field from several hundreds of neurons around the electrode tip. LFP recordings can be maintained for longer periods of time than single cell recordings. We find that similar information can be decoded from LFP and spike recordings, with better performance for state decodes with LFPs and, depending on the area, equivalent or slightly less than equivalent performance for signaling the direction of planned movements. Movable electrodes in microdrives can be adjusted in the tissue to optimize recordings, but their movements must be automated to be a practical benefit to patients. We have developed automation algorithms and a meso-scale autonomous electrode testbed, and demonstrated that this system can autonomously isolate and maintain the recorded signal quality of single cells in the cortex of awake, behaving monkeys. These two advances show promise for developing very long term recording for neural prosthetic applications."],["dc.identifier.doi","10.1109/iembs.2004.1404494"],["dc.identifier.gro","3151410"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8209"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","chake"],["dc.publisher","IEEE"],["dc.relation.isbn","0-7803-8439-3"],["dc.relation.ispartof","The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society"],["dc.title","Recording advances for neural prosthetics"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","463"],["dc.bibliographiccitation.lastpage","474"],["dc.contributor.author","Andersen, Richard A."],["dc.contributor.author","Meeker, D."],["dc.contributor.author","Pesaran, B."],["dc.contributor.author","Buneo, C."],["dc.contributor.author","Scherberger, H."],["dc.contributor.author","Breznen, Boris"],["dc.contributor.editor","Gazzaniga, M. S."],["dc.date.accessioned","2017-11-20T15:53:40Z"],["dc.date.available","2017-11-20T15:53:40Z"],["dc.date.issued","2004"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10106"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","MIT Press"],["dc.publisher.place","Cambridge"],["dc.relation.ispartof","The Cognitive Neurosciences III"],["dc.title","Senosorimotor transformations in the posterior parietal cortex"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","258"],["dc.bibliographiccitation.issue","5681"],["dc.bibliographiccitation.journal","Science"],["dc.bibliographiccitation.lastpage","262"],["dc.bibliographiccitation.volume","305"],["dc.contributor.author","Musallam, S."],["dc.contributor.author","Corneil, B. D."],["dc.contributor.author","Greger, B."],["dc.contributor.author","Scherberger, Hansjörg"],["dc.contributor.author","Andersen, Richard A."],["dc.date.accessioned","2017-09-07T11:54:34Z"],["dc.date.available","2017-09-07T11:54:34Z"],["dc.date.issued","2004"],["dc.description.abstract","Recent development of neural prosthetics for assisting paralyzed patients has focused on decoding intended hand trajectories from motor cortical neurons and using this signal to control external devices. In this study, higher level signals related to the goals of movements were decoded from three monkeys and used to position cursors on a computer screen without the animals emitting any behavior. Their performance in this task improved over a period of weeks. Expected value signals related to fluid preference, the expected magnitude, or probability of reward were decoded simultaneously with the intended goal. For neural prosthetic applications, the goal signals can be used to operate computers, robots, and vehicles, whereas the expected value signals can be used to continuously monitor a paralyzed patient's preferences and motivation."],["dc.identifier.doi","10.1126/science.1097938"],["dc.identifier.gro","3151438"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8239"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","chake"],["dc.relation.issn","0036-8075"],["dc.title","Cognitive Control Signals for Neural Prosthetics"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1324"],["dc.bibliographiccitation.lastpage","1336"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Scherberger, Hansjörg"],["dc.contributor.author","Andersen, Richard A."],["dc.contributor.editor","Chalupa, Leo M."],["dc.contributor.editor","Werner, John Simon"],["dc.date.accessioned","2017-11-20T16:02:35Z"],["dc.date.available","2017-11-20T16:02:35Z"],["dc.date.issued","2003"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10108"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","MIT Press"],["dc.publisher.place","Cambridge"],["dc.relation.isbn","0-262-03308-9"],["dc.relation.isbn","978-0-262-03308-4"],["dc.relation.ispartof","The Visual Neurosciences"],["dc.title","Sensorimotor Transformation in the Posterior Parietal Cortex"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","347"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Neuron"],["dc.bibliographiccitation.lastpage","354"],["dc.bibliographiccitation.volume","46"],["dc.contributor.author","Scherberger, Hansjörg"],["dc.contributor.author","Jarvis, Murray R."],["dc.contributor.author","Andersen, Richard A."],["dc.date.accessioned","2017-09-07T11:53:56Z"],["dc.date.available","2017-09-07T11:53:56Z"],["dc.date.issued","2005"],["dc.description.abstract","The cortical local field potential (LFP) is a summation signal of excitatory and inhibitory dendritic potentials that has recently become of increasing interest. We report that LFP signals in the parietal reach region (PRR) of the posterior parietal cortex of macaque monkeys have temporal structure that varies with the type of planned or executed motor behavior. LFP signals from PRR provide better decode performance for reaches compared to saccades and have stronger coherency with simultaneously recorded spiking activity during the planning of reach movements than during saccade planning. LFP signals predict the animal’s behavioral state (e.g., planning a reach or saccade) and the direction of the currently planned movement from single-trial information. This new evidence provides further support for a role of the parietal cortex in movement planning and the potential application of LFP signals for a brain-machine interface."],["dc.identifier.doi","10.1016/j.neuron.2005.03.004"],["dc.identifier.gro","3151419"],["dc.identifier.pmid","15848811"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8219"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0896-6273"],["dc.title","Cortical Local Field Potential Encodes Movement Intentions in the Posterior Parietal Cortex"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2001"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","The Journal of neuroscience"],["dc.bibliographiccitation.lastpage","2012"],["dc.bibliographiccitation.volume","27"],["dc.contributor.author","Scherberger, Hansjörg"],["dc.contributor.author","Andersen, Richard A."],["dc.date.accessioned","2017-09-07T11:54:32Z"],["dc.date.available","2017-09-07T11:54:32Z"],["dc.date.issued","2007"],["dc.description.abstract","The selection of visual stimuli as a target for a motor action may depend on external as well as internal variables. The parietal reach region (PRR) in the posterior parietal cortex plays an important role in the transformation of visual information into reach movement plans. We asked how neurons in PRR of macaque monkeys reflect the decision process of selecting one of two visual stimuli as a target for a reach movement. Spiking activity was recorded while the animal performed a free-choice task with one target presented in the preferred direction and the other in the off direction of the cell. Stimulus-onset asynchrony (SOA) was adjusted to ensure that both targets were selected equally often and the amount of reward was fixed. Neural activity in PRR was action specific for arm reaching and reflected the timing of the SOA as well as the selection of reach targets. In individual trials, activity was strongly linked to the choice of the animal, and, for the majority of cells, target selections could be predicted from activity in the stimulation or planning period, i.e., before the movement started. Many neurons were gain modulated by the fixation position, but gain modulation did not influence the target selection process directly. Finally, it was found that target selection for saccade movements was only weakly represented in PRR. These findings suggest that PRR is involved in decision making for reach movements and that separate cortical networks exist for target selection of different types of action."],["dc.identifier.doi","10.1523/jneurosci.4274-06.2007"],["dc.identifier.gro","3151432"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8234"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","0270-6474"],["dc.title","Target Selection Signals for Arm Reaching in the Posterior Parietal Cortex"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]