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Heinze, H.-J.

Publications and source records attributed to Heinze, H.-J..

5 recordsLinked to original sources

Altered Dynamics of Cortical Beta-Oscillations during Motor Learning in Cerebellar Ataxia

Cerebellar ataxia is associated with an implicit motor learning dysfunction, specifically, a miscalibration of internal models relating motor commands to state changes of the body. Explicit cognitive strategies could compensate for deficits in implicit calibration. Surprisingly, however, patients with cerebellar ataxia use insufficient strategies compared to healthy controls. We report a candidate physiological phenomenon of disrupted strategy use in cerebellar ataxia, reflected in an interaction of implicit and explicit learning effects on cortical beta oscillations. We recorded electroencephalography in patients with cerebellar ataxia (n=18), age-matched healthy controls (n=19), and young, healthy individuals (n=34) during a visuomotor rotation paradigm in which an aiming strategy was either explicitly instructed, or had to be discovered through learning. In young, healthy individuals, learning a strategy, but not implicit learning from sensory prediction error alone, decreased the post-movement beta rebound. Disrupted learning from sensory prediction error in patients, on the other hand, unmasked effects of explicit and implicit control that are normally balanced. Specifically, the post-movement beta rebound increased during strategy use when implicit learning was disrupted, i.e., in patients, but not controls. We conclude that a network disturbance due to cerebellar degeneration surfaces in imbalanced cortical beta oscillations normally involved in strategy learning.

neuroscience↗

Decoding the covert shift of spatial attention from electroencephalographic signals permits reliable control of a brain-computer interface

ObjectiveOne of the main goals of brain-computer interfaces (BCI) is to restore communication abilities in patients. BCIs often use event-related potentials (ERPs) like the P300 which signals the presence of a target in a stream of stimuli. The P300 and related approaches, however, are inherently limited, as they require many stimulus presentations to obtain a usable control signal. Many approaches depend on gaze-direction to focus the target, which is also not a viable approach in many cases, because eye movements might be impaired in potential users. Here we report on a BCI that avoids both shortcomings by decoding spatial target information, independent of gaze shifts. ApproachWe present a new method to decode from the electroencephalogram (EEG) covert shifts of attention to one out of four targets simultaneously presented in the left and right visual field. The task is designed to evoke the N2pc component - a hemisphere lateralized response, elicited over the occipital scalp contralateral to the attended target. The decoding approach involves decoding of the N2pc based on data-driven estimation of spatial filters and a correlation measure. Main resultsDespite variability of decoding performance across subjects, 22 out of 24 subjects performed well above chance level. Six subjects even exceeded 80% (cross-validated: 89%) correct predictions in a four-class discrimination task. Hence, the single-trial N2pc proves to be a component that allows for reliable BCI control. An offline analysis of the EEG data with respect to their dependence on stimulation time and number of classes demonstrates that the present method is also a workable approach for two-class tasks. SignificanceOur method extends the range of strategies for gaze-independent BCI control. The proposed decoding approach has the potential to be efficient in similar applications intended to decode ERPs.

neuroscience↗

Local sleep during mind-wandering enhances processes of spatial attention allocation

Mind wandering (MW) is a subjective, cognitive phenomenon, in which thoughts move away from the task towards an internal train of thoughts, possibly during phases of neuronal sleep-like activity (local sleep, LS). MW decreases cortical processing of external stimuli and is assumed to decouple attention from the external world. Here, we directly tested how indicators of LS, cortical processing and attentional selection change in a pop-out visual search task during phases of MW. Participants brain activity was recorded using magnetoencephalography, MW was assessed via self-report using randomly interspersed probes. As expected, MW worsened performance being accompanied by a decrease in high frequency activity (HFA, 80-150Hz) and an increase in slow wave activity (SWA, 1-6Hz), consistent with the occurrence of LS. In contrast, visual attentional selection as indexed by the N2pc component was enhanced during MW with the N2pc amplitude being directly linked to participants performance. This observation clearly contradicts accounts of attentional decoupling predicting a decrease in attention-related responses to external stimuli during MW. Together our results suggest that MW occurs during phases of LS with processes of attentional target selection being upregulated, potentially to compensate for the mental distraction during MW.

neuroscience↗

Multiscale criticality measures as general-purpose gauges of proper brain function

The brain is universally regarded as a system for processing information. If so, any behavioral or cognitive dysfunction should lend itself to depiction in terms of information processing deficiencies. Information is characterized by recursive, hierarchical complexity. The brain accommodates this complexity by a hierarchy of large/slow and small/fast spatiotemporal loops of activity. Thus, successful information processing hinges upon tightly regulating the spatiotemporal makeup of activity, to optimally match the underlying multiscale delay structure of such hierarchical networks. Reduced capacity for information processing will then be expressed as deviance from this requisite multiscale character of spatiotemporal activity. This deviance is captured by a general family of multiscale criticality measures (MsCr). We applied MsCr to MEG and EEG data in four telling degraded information processing scenarios: disorders of consciousness, mild cognitive impairment, schizophrenia and preictal activity. Consistently with our previous modeling work, MsCr measures systematically varied with information processing capacity. MsCr measures might thus be able to serve as general gauges of information processing capacity and, therefore, as normative measures of brain health.

neuroscience↗

Direct evidence for prediction signals in frontal cortex independent of prediction error

Predictive coding (PC) has been suggested as one of the main mechanisms used by brains to interact with complex environments. PC theories posit top-down prediction signals, which are compared with actual outcomes, yielding in turn prediction-error signals, which are used, bottom-up, to modify the ensuing predictions. However, disentangling prediction from prediction-error signals has been challenging. Critically, while many studies found indirect evidence for predictive coding in the form of prediction-error signals, direct evidence for the prediction signal is mostly lacking. Here we provide clear evidence, obtained from intracranial cortical recordings in human surgical patients, that the human lateral prefrontal cortex generates prediction signals while anticipating an event. Patients listened to task-irrelevant sequences of repetitive tones including infrequent predictable or unpredictable pitch deviants. The amplitude of high frequency broadband (HFB) neural activity was decreased prior to the onset of expected relative to unexpected deviants in the frontal cortex only, and its amplitude was sensitive to the increasing likelihood of deviants following longer trains of standards in the unpredictable condition. Single trial HFB amplitudes predicted deviations and correlated with post-stimulus response to deviations. These results provide direct evidence for frontal cortex prediction signals independent of prediction-error signals.

neuroscience↗