Gail, Alexander

[["dc.bibliographiccitation.artnumber","P116"],["dc.bibliographiccitation.issue","Suppl 1"],["dc.bibliographiccitation.journal","BMC Neuroscience"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Klaes, Christian"],["dc.contributor.author","Schneegans, Sebastian"],["dc.contributor.author","Schöner, Gregor"],["dc.contributor.author","Gail, Alexander"],["dc.date.accessioned","2011-07-22T22:26:02Z"],["dc.date.accessioned","2011-07-23T15:34:57Z"],["dc.date.accessioned","2021-10-27T13:12:55Z"],["dc.date.available","2011-07-22T22:26:02Z"],["dc.date.available","2011-07-23T15:34:57Z"],["dc.date.available","2021-10-27T13:12:55Z"],["dc.date.issued","2011"],["dc.date.updated","2011-07-22T22:26:02Z"],["dc.identifier.doi","10.1186/1471-2202-12-S1-P116"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6833"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/91734"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.relation.orgunit","Deutsches Primatenzentrum"],["dc.rights","CC BY 2.0"],["dc.rights.holder","et al.; licensee BioMed Central Ltd."],["dc.rights.uri","https://creativecommons.org/licenses/by/2.0"],["dc.subject.ddc","599"],["dc.subject.ddc","599.8"],["dc.title","A neural field model of decision making in the posterior parietal cortex"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","9490"],["dc.bibliographiccitation.issue","30"],["dc.bibliographiccitation.journal","The Journal of neuroscience"],["dc.bibliographiccitation.lastpage","9499"],["dc.bibliographiccitation.volume","29"],["dc.contributor.author","Gail, Alexander"],["dc.contributor.author","Klaes, Christian"],["dc.contributor.author","Westendorff, Stephanie"],["dc.date.accessioned","2017-09-07T11:47:44Z"],["dc.date.available","2017-09-07T11:47:44Z"],["dc.date.issued","2009"],["dc.description.abstract","Planning goal-directed movements requires the combination of visuospatial with abstract contextual information. Our sensory environment constrains possible movements to a certain extent. However, contextual information guides proper choice of action in a given situation and allows flexible mapping of sensory instruction cues onto different motor actions. We used anti-reach tasks to test the hypothesis that spatial motor-goal representations in cortical sensorimotor areas are gain modulated by the behavioral context to achieve flexible remapping of spatial cue information onto arbitrary motor goals. We found that gain modulation of neuronal reach goal representations is commonly induced by the behavioral context in individual neurons of both, the parietal reach region (PRR) and the dorsal premotor cortex (PMd). In addition, PRR showed stronger directional selectivity during the planning of a reach toward a directly cued goal (pro-reach) compared with an inferred target (anti-reach). PMd, however, showed stronger overall activity during reaches toward inferred targets compared with directly cued targets. Based on our experimental evidence, we suggest that gain modulation is the computational mechanism underlying the integration of spatial and contextual information for flexible, rule-driven stimulus–response mapping, and thereby forms an important basis of goal-directed behavior. Complementary contextual effects in PRR versus PMd are consistent with the idea that posterior parietal cortex preferentially represents sensory-driven, “automatic” motor goals, whereas frontal sensorimotor areas are stronger engaged in the representation of rule-based, “inferred” motor goals."],["dc.identifier.doi","10.1523/jneurosci.1095-09.2009"],["dc.identifier.gro","3150713"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7500"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.relation.issn","0270-6474"],["dc.title","Implementation of Spatial Transformation Rules for Goal-Directed Reaching via Gain Modulation in Monkey Parietal and Premotor Cortex"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e1002774"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Klaes, Christian"],["dc.contributor.author","Schneegans, Sebastian"],["dc.contributor.author","Schöner, Gregor"],["dc.contributor.author","Gail, Alexander"],["dc.contributor.editor","Sporns, Olaf"],["dc.date.accessioned","2017-09-07T11:47:47Z"],["dc.date.available","2017-09-07T11:47:47Z"],["dc.date.issued","2012"],["dc.description.abstract","According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations."],["dc.identifier.doi","10.1371/journal.pcbi.1002774"],["dc.identifier.gro","3150716"],["dc.identifier.pmid","23166483"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8431"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7503"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.relation.issn","1553-7358"],["dc.rights","CC BY 2.5"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.5"],["dc.title","Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","536"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Neuron"],["dc.bibliographiccitation.lastpage","548"],["dc.bibliographiccitation.volume","70"],["dc.contributor.author","Klaes, Christian"],["dc.contributor.author","Westendorff, Stephanie"],["dc.contributor.author","Chakrabarti, Shubhodeep"],["dc.contributor.author","Gail, Alexander"],["dc.date.accessioned","2017-09-07T11:47:46Z"],["dc.date.available","2017-09-07T11:47:46Z"],["dc.date.issued","2011"],["dc.description.abstract","In natural situations, movements are often directed toward locations different from that of the evoking sensory stimulus. Movement goals must then be inferred from the sensory cue based on rules. When there is uncertainty about the rule that applies for a given cue, planning a movement involves both choosing the relevant rule and computing the movement goal based on that rule. Under these conditions, it is not clear whether primates compute multiple movement goals based on all possible rules before choosing an action, or whether they first choose a rule and then only represent the movement goal associated with that rule. Supporting the former hypothesis, we show that neurons in the frontoparietal reach areas of monkeys simultaneously represent two different rule-based movement goals, which are biased by the monkeys' choice preferences. Apparently, primates choose between multiple behavioral options by weighing against each other the movement goals associated with each option."],["dc.identifier.doi","10.1016/j.neuron.2011.02.053"],["dc.identifier.gro","3150723"],["dc.identifier.pmid","21555078"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7511"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.relation.issn","0896-6273"],["dc.title","Choosing Goals, Not Rules: Deciding among Rule-Based Action Plans"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","5426"],["dc.bibliographiccitation.issue","15"],["dc.bibliographiccitation.journal","The Journal of neuroscience"],["dc.bibliographiccitation.lastpage","5436"],["dc.bibliographiccitation.volume","30"],["dc.contributor.author","Westendorff, Stephanie"],["dc.contributor.author","Klaes, Christian"],["dc.contributor.author","Gail, Alexander"],["dc.date.accessioned","2017-09-07T11:47:48Z"],["dc.date.available","2017-09-07T11:47:48Z"],["dc.date.issued","2010"],["dc.description.abstract","Flexible sensorimotor planning is the basis for goal-directed behavior. We investigated the integration of visuospatial information with context-specific transformation rules during reach planning. We were especially interested in the relative timing of motor-goal decisions in monkey dorsal premotor cortex (PMd) and parietal reach region (PRR). We used a rule-based mapping task with different cueing conditions to compare task-dependent motor-goal latencies. The task allowed us a separation of cue-related from motor-related activity, and a separation of activity related to motor planning from activity related to motor initiation or execution. The results show that selectivity for the visuospatial goal of a pending movement occurred earlier in PMd than PRR whenever the task required spatial remapping. Such remapping was needed if the spatial representation of a cue or of a default motor plan had to be transformed into a spatially incongruent representation of the motor goal. In contrast, we did not find frontoparietal latency differences if the spatial representation of the cue or the default plan was spatially congruent with the motor goal. The fact that frontoparietal latency differences occurred only in conditions with spatial remapping was independent of the subjects' partial a priori knowledge about the pending goal. Importantly, frontoparietal latency differences existed for motor-goal representations during movement planning, without immediate motor execution. We interpret our findings as being in support of the hypothesis that latency differences reflect a dynamic reorganization of network activity in PRR, and suggest that the reorganization is contingent on frontoparietal projections from PMd."],["dc.identifier.doi","10.1523/jneurosci.4628-09.2010"],["dc.identifier.gro","3150731"],["dc.identifier.pmid","20392964"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7520"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.relation.issn","0270-6474"],["dc.title","The Cortical Timeline for Deciding on Reach Motor Goals"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]