From biological variation to goal-directed action
A year in research · 14 selected publications · five research threads
In 2013, we established how genes, brain asymmetries, stress and striatal dynamics shape the selection and evaluation of actions.
These studies combined genetics, EEG, imaging and behavioural tasks to explain why people differ in multitasking, inhibition, lateralization and adaptation.
01 · CASCADED ACTIONS
Functional imaging showed that striatal activation determines how much stopping and changing overlap on a serial-to-parallel continuum during cascaded actions.[1] Motivation changed that balance in opposite directions: punishment sped dual-task performance, whereas reward slowed it.[2] Acute stress also improved dual-task efficiency by changing how tasks were processed rather than how the central bottleneck switched between them.[3]
Together, these findings framed multi-action control as a flexible scheduling problem shaped by basal ganglia and current goals.
In plain terms: Coordinating several actions depends on how strongly their task goals overlap, and that overlap can be shifted by motivation and state.
02 · MONITORING
Response evaluation drew differently on outgoing motor-command copies and incoming proprioceptive information.[4] Variation in the neuropeptide S receptor was related to better inhibition and stronger error monitoring, linking an anxiety-relevant system to a potential neurophysiological endophenotype.[5]
A longitudinal EEG measure in premanifest Huntington's disease tracked progression and predicted clinically relevant parameters more sensitively than established measures.[6] This work showed the translational value of mechanism-based signals.
In plain terms: Sensitive monitoring measures can distinguish intended, executed and evaluated aspects of an action—and can track disease before overt symptoms dominate.
03 · GENES AND AGEING
In healthy older adults, the BDNF Val66Met polymorphism changed vulnerability to auditory distraction through frontostriatal processes.[7] A functional TNF-alpha variant was associated with slower attentional selection, greater distractibility and weaker response selection, connecting inflammatory signalling to ageing cognition.[8]
These findings demonstrated that a genetic effect becomes meaningful only through the processing operation and population in which it is expressed.
In plain terms: Genes do not encode a fixed level of control; they bias particular processes under particular developmental and environmental conditions.
04 · LATERALIZATION
CCK receptor and FOXP2 variation were associated with individual differences in language lateralization.[9,10] A PCSK6 repeat polymorphism related to the degree, but not the direction, of handedness.[11] A broader review therefore argued for a multifactorial model in which several genes and environmental influences jointly shape handedness.[12]
Functional asymmetry was behaviourally relevant beyond language: right-lateralized facial-expression processing modulated subsequent response inhibition.[13]
In plain terms: Cerebral asymmetries emerge from multiple biological pathways, and early lateralized perception can influence later executive action.
05 · PLASTICITY
A synthesis of sensory-plasticity research showed that intensive task training is not always required for learning; stimulation protocols can instead be optimized to alter synaptic transmission and efficacy.[14]
Placed beside the year's work on genes, state and basal ganglia, this broadened the lab's account of adaptation: behaviour changes through both deliberate practice and the biological tuning of information-processing systems.
In plain terms: Plasticity can be induced through structured sensory exposure even without explicit task training.
The 2013 programme connected biological variability to the organization of goal-directed action. It laid foundations for later work by treating control as a set of measurable operations shaped by striatum, body, context and development.
Curated from PubMed records returned for Beste C[au] in 2013. Citation numbers in the story link to entries below. DOI links open the publisher landing page; PubMed links open the indexed record.
Ness V, Beste C. Neuropsychologia. 2013;51(13):2562-71.
DOI: 10.1016/j.neuropsychologia.2013.09.032 · PubMed
Yildiz A, Chmielewski W, Beste C. Behavioural brain research. 2013;250:304-7.
DOI: 10.1016/j.bbr.2013.05.010 · PubMed
Beste C, Yildiz A, Meissner TW, Wolf OT. Behavioural brain research. 2013;252:260-5.
DOI: 10.1016/j.bbr.2013.06.013 · PubMed
Stock AK, Wascher E, Beste C. PloS one. 2013;8(4):e62335.
DOI: 10.1371/journal.pone.0062335 · PubMed
Beste C, Konrad C, Uhlmann C, Arolt V, Zwanzger P, Domschke K. NeuroImage. 2013;71:1-9.
DOI: 10.1016/j.neuroimage.2013.01.004 · PubMed
Beste C, Stock AK, Ness V, Hoffmann R, Lukas C, Saft C. Scientific reports. 2013;3:1797.
DOI: 10.1038/srep01797 · PubMed
Getzmann S, Gajewski PD, Hengstler JG, Falkenstein M, Beste C. NeuroImage. 2013;64:290-8.
DOI: 10.1016/j.neuroimage.2012.08.079 · PubMed
Gajewski PD, Hengstler JG, Golka K, Falkenstein M, Beste C. Neurobiology of aging. 2013;34(11):2694.e1-2694.e12.
DOI: 10.1016/j.neurobiolaging.2013.04.017 · PubMed
Ocklenburg S, Arning L, Gerding WM, Epplen JT, Güntürkün O, Beste C. PloS one. 2013;8(1):e53643.
DOI: 10.1371/journal.pone.0053643 · PubMed
Ocklenburg S, Arning L, Gerding WM, Epplen JT, Güntürkün O, Beste C. Brain and language. 2013;126(3):279-84.
DOI: 10.1016/j.bandl.2013.07.001 · PubMed
Arning L, Ocklenburg S, Schulz S, Ness V, et al.. PloS one. 2013;8(6):e67251.
DOI: 10.1371/journal.pone.0067251 · PubMed
Ocklenburg S, Beste C, Güntürkün O. Neuroscience and biobehavioral reviews. 2013;37(10 Pt 2):2788-93.
DOI: 10.1016/j.neubiorev.2013.09.014 · PubMed
Ocklenburg S, Ness V, Güntürkün O, Suchan B, Beste C. Frontiers in psychology. 2013;4:879.
DOI: 10.3389/fpsyg.2013.00879 · PubMed
Beste C, Dinse HR. Current biology : CB. 2013;23(11):R489-99.
DOI: 10.1016/j.cub.2013.04.044 · PubMed