News
19.06.2013
The next date of the research colloquium is Monday, 08.07.2013,
1 - 3 pm in GAFO 05/425, with the talk "Mechanisms of hemispheric specialization: Analyses of functional brain connectivity" of Andreas Jansen
(Universitätsklinikum, Standort Marburg) .
07.06.2013
Studentische oder Wissenschaftliche Hilfskräfte gesucht!
27.05.2013
We are inviting applications for three Postdoctoral positions (either in in-vivo electrophysiology, small animal imaging, Neuroanatomy, or Animal Cognition) at the Biopsychology Laboratory, Institute of Cognitive Neuroscience, Ruhr-University Bochum (Germany) for research on the
“Neuronal Fundaments of Cognition and Brain Asymmetries in Birds”.
Contact
Ruhr-Universität Bochum
Fakultät für Psychologie
AE Biopsychologie
GAFO 05/618
D-44780 Bochum
Phone: +49 - 234 - 32 - 28213
Fax: +49 - 234 - 32 - 14377
Email: biopsychologie@rub.de
Homepage: http://www.bio.psy.rub.de
News & Views
Inaugural Lecture of Christian Beste
On the 5th of June 2013 Christian Beste gave his inaugural lecture on "Cognitive Neurophysiology of Action Control: Between Basic and Applied Science". It was a fantastic tour de force of neuroscientific experiments that proceeded all the way from cells to patients. With this lecture the process of habilitation is now officially completed.
Congratulations Christian!
News & Views
Marsilius Medal for Onur Güntürkün
The Marsilius Lectures are activities for the academic community of all disciplines as well as for the broader public. Once a semester, the Marsilius Kolleg invites a well-known scientist to speak about a topic that calls for bridging the gaps between scholarly cultures. In recognition of their achievements in the dialogue between scholarly cultures, the speakers of the Marsilius Lecture are decorated with the Marsilius Medal. This May it was Onur’s turn. In a stunningly baroque and huge lecture hall he spoke about “Die Evolution des Denkens”. Afterwards he was awarded with the Marsilius Medal.
News & Views
Cortical Excitability does not Predict Learning and Improvisation of Complex Motor Tasks
The excitability of our cortex varies between individual and over time. Does this variability affect learning speed and even behavioral variability? Indeed, facilitation of motor cortical excitability has been shown to be positively correlated with improvements in performance in simple motor tasks. Thus cortical excitability may tentatively be considered as a marker of learning and use-dependent plasticity. Previous studies focused on changes in cortical excitability brought about by learning processes, however, the relation between native levels of cortical excitability on the one hand and brain activation and behavioral parameters on the other is as yet unknown. A team of Neurologists and Biopsychologists from Bochum now investigated the role of differential native motor cortical excitability for learning a motor sequencing task. The motor task required the participants to reproduce and improvise over a pre-learned piano sequence. Over both task conditions, participants with low cortical excitability showed significantly higher BOLD activation in task-relevant brain regions than participants with high cortical excitability. In contrast, both groups did not exhibit differences in learned performance and improvisation level. Moreover, cortical excitability did practically not change after learning and training in either group. The present data suggest that the native, unmanipulated level of cortical excitability is related to brain activation intensity, but not to performance quality. Possibly, the subjects with the lower cortical excitability possibly only showed a higher BOLD signal intensity to compensate for their lower level of excitation.
News & Views
Learning without training
It sounds like an old dream is becoming true. Recent work suggests that intensive training may not be necessary for skill learning. Skills can be effectively acquired by a complementary approach in which the learning occurs in response to mere exposure to repetitive sensory stimulation. Such training-independent sensory learning induces lasting changes in perception and goal directed behaviour in humans, without any explicit task training. We suggest that the effectiveness of this form of learning in different sensory domains stems from the fact that the stimulation protocols used are optimized to alter synaptic transmission and efficacy. While this approach directly links behavioural research in humans with studies on cellular plasticity, other approaches show that learning can occur even in the absence of an actual stimulus. These include learning through imagery or feedback-induced cortical activation, resulting in learning without task training. All these approaches challenge our understanding of the mechanisms that mediate learning. Apparently, humans can learn under conditions thought to be impossible a few years ago. Although the underlying mechanisms are far from being understood, training-independent sensory learning opens novel possibilities for applications aimed at augmenting human cognition.
Beste, C., Dinse, H.R. (2013). Learning without training. Curr Biol, 23, 489-499.
News & Views
AS GOOD AS IT GETS: PIGEONS USE A NON-OPTIMAL CHOICE STRATEGY TO ADAPT BEHAVIOR
A vast body of data supports the notion that animals, including humans, perform statistically optimally in a wide range of tasks, supporting the claim that evolution has shaped the nervous system of organisms in a way that yields maximally adaptive behavior. Optimality is frequently assessed by comparing behavioral output to benchmarks computed via methods derived from statistical decision theory. Such methods have also been used to assess the reliability of sensory neural signals, and have even been invoked as accounts of neural processing.
Scientists from the Biopsychology lab have explicitly tested the claim of optimality with pigeons performing a perceptual choice task with varying reward probabilities. Surprisingly, the pattern of choices observed was opposite to that expected under an optimization account. This finding poses important constraints on the class of algorithms useful for modeling adaptive choice behavior. Furthermore, the algorithm which fit the data best was learning exclusively on correct trials ending in reward, as opposed to algorithms learning from both reward and errors. Put simply, the pigeons seem to learn from reward, but not from errors - at least when performing a psychophysical task.