Circuits for presaccadic remapping

Saccadic eye movements rapidly displace the image of the world that is projected onto the retinas. In anticipation of each saccade, many neurons in the visual system shift their receptive fields. This presaccadic change in visual sensitivity, known as remapping, was first documented in the parietal cortex and has been studied in many other brain regions. Remapping requires information about upcoming saccades via corollary discharge. Analyses of neurons in a corollary discharge pathway that targets the frontal eye field (FEF) suggest that remapping may be assembled in the FEF’s local microcircuitry. Complementary data from reversible inactivation, neural recording, and modeling studies provide evidence that remapping contributes to transsaccadic continuity of action and perception. Multiple forms of remapping have been reported in the FEF and other brain areas, however, and questions remain about reasons for these differences. In this review of recent progress, we identify three hypotheses that may help to guide further investigations into the structure and function of circuits for remapping.

Circuits for Presaccadic Visual Remapping.

Saccadic eye movements rapidly displace the image of the world that is projected onto the retinas. In anticipation of each saccade, many neurons in the visual system shift their receptive fields. This presaccadic change in visual sensitivity, known as remapping, was first documented in the parietal cortex and has been studied in many other brain regions. Remapping requires information about upcoming saccades via corollary discharge. Analyses of neurons in a corollary discharge pathway that targets the frontal eye field (FEF) suggest that remapping may be assembled in the FEF's local microcircuitry. Complementary data from reversible inactivation, neural recording, and modeling studies provide evidence that remapping contributes to transsaccadic continuity of action and perception. Multiple forms of remapping have been reported in the FEF and other brain areas, however, and questions remain about reasons for these differences. In this review of recent progress, we identify three hypotheses that may help to guide further investigations into the structure and function of circuits for remapping.

Introduction of novel video-based tasks to clinical fMRI: Comparing traditional fMRI tasks with novel video-based tasks for mapping brain language areas

Recently, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has become a routine clinical procedure for localization of language and motor brain regions and has been replacing more invasive preoperative procedures. However, the fMRI results from these tasks are not always reproducible even from the same patient. Evaluating the reproducibility of language and speech mapping is especially complicated due to the complex brain circuitry that may become activated during the functional task. Non-language areas such as sensory, attention, decision-making, and motor brain regions may also be activated in addition to the specific language regions during a traditional sentence-completion task. In this study, I test a new approach, which utilizes 4-minute video-based tasks, to map language and speech brain regions for patients undergoing brain surgery. Results from 35 subjects have shown that the video-based task activates Wernicke’s area, as well as Broca’s area in most subjects. The computed laterality indices, which indicate the dominant hemisphere from that functional task, have indicated left dominance from the video-based tasks. This study has shown that the video-based task may be an alternative method for localization of language and speech brain regions for patients who are unable to complete the sentence-completion task.

Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.