The automatic brain: studies on practice and brain function in healthy subjects and patients with schizophrenia

Practice makes perfect. The neural mechanisms behind the behavioral improvement of practice (automatization) however are largely unknown. Here we investigate how practice changes brain function and how this can improve our processing capacity. We also examine whether a deficit in automatization can explain the severely limited processing capacity in schizophrenia. Previous research implicates working memory (WM) in the development of automatization and the ability to improve processing capacity with practice. The course of activity changes in brain regions important for WM following practice for distinct behavioral components however is poorly understood. We show that practice induces heterogeneous changes in WM activation for information encoding and responding to information. Practice predominantly facilitates information encoding and thereby possibly improves the capacity to process otherwise interfering information. Another question pertains to whether decreases in activity in brain areas important for WM are accompanied by compensatory changes elsewhere in the brain. We show that practice neither leads to a shift from one network to another, nor to a gain in involvement of regions within the initially active network(s). Practice thus induces a general decline in the WM system without compensatory changes elsewhere in the brain. This may suggest that WM allows restructuring of information that allows more efficient processing following practice as encoding strategies performed by WM decrease. By selectively interfering with activity in brain regions important for WM we investigated the critical importance of WM for automatization. We show that automatization diminishes critical contributions of WM to performance and that with sufficient practice, performance may become independent of cognitive control. This supports the idea that WM engages in restructuring of information when performance is novel, thereby enabling more efficient processing as WM slowly disengages over the course of practice. Patients with schizophrenia typically exhibit inefficient brain function when task load is within the boundaries of their capacity. We investigated whether a failure in automatization can explain inefficient WM function and reduced capacity in schizophrenia. Although patients showed increased (and thus inefficient) brain activity during novel performance, automatization was not impaired. In addition, there was no clear relationship between automatization and the deficit in patients to concurrently perform two tasks. The results suggest that inefficient WM function and reduced capacity in schizophrenia are associated with a failure to properly engage WM when task demands are high for instance during novel performance and when performing an additional task concurrently when goals require frequent updating. This research shows that automatization involves a dynamic distribution of processing resources that allows organizing and structuring of the large amounts of complex information present in our environment. This enables more efficient processing, thereby possibly increasing the capacity to process otherwise interfering information. Severely limited processing capacity in schizophrenia however was not explained by a deficit in automatization. Here we postulate that due to an inability to process frequently changing information, patients with schizophrenia will tend to engage in automatic behaviors, resulting in limited capacity to process information that require flexible and adaptive cognitive strategies

fMRI guided rTMS evidence for reduced left prefrontal involvement after task practice

Contains fulltext : 130274.pdf (publisher's version ) (Open Access)Introduction: Cognitive tasks that do not change the required response for a stimulus over time ('consistent mapping') show dramatically improved performance after relative short periods of practice. This improvement is associated with reduced brain activity in a large network of brain regions, including left prefrontal and parietal cortex. The present study used fMRI-guided repetitive transcranial magnetic stimulation (rTMS), which has been shown to reduce processing efficacy, to examine if the reduced activity in these regions also reflects reduced involvement, or possibly increased efficiency. Methods: First, subjects performed runs of a Sternberg task in the scanner with novel or practiced target-sets. This data was used to identify individual sites for left prefrontal and parietal peak brain activity, as well as to examine the change in activity related to practice. Outside of the scanner, real and sham rTMS was applied at left prefrontal and parietal cortex to examine their involvement novel and practiced conditions. Results: Prefrontal as well as parietal rTMS significantly reduced target accuracy for novel targets. Prefrontal, but not parietal, rTMS interference was significantly lower for practiced than novel target-sets. rTMS did not affect nontarget accuracy, or reaction time in any condition. Discussion: These results show that task practice in a consistent environment reduces involvement of the prefrontal cortex. Our findings suggest that prefrontal cortex is predominantly involved in target maintenance and comparison, as rTMS interference was only detectable for targets. Findings support process switching hypotheses that propose that practice creates the possibility to select a response without the need to compare with target items. Our results also support the notion that practice allows for redistribution of limited maintenance resources.11 p

Developmental differences in higher-order resting-state networks in autism spectrum disorder

Neuro Imaging Researc

Developmental differences in higher-order resting-state networks in autism spectrum disorder

Neuro Imaging Researc