Tools for interfacing, extracting, and analyzing neural signals using wide-field fluorescence imaging and optogenetics in awake behaving mice

Imaging of multiple cells has rapidly multiplied the rate of data acquisition as well as our knowledge of the complex dynamics within the mammalian brain. The process of data acquisition has been dramatically enhanced with highly affordable, sensitive image sensors enable high-throughput detection of neural activity in intact animals. Genetically encoded calcium sensors deliver a substantial boost in signal strength and in combination with equally critical advances in the size, speed, and sensitivity of image sensors available in scientific cameras enables high-throughput detection of neural activity in behaving animals using traditional wide-field fluorescence microscopy. However, the tremendous increase in data flow presents challenges to processing, analysis, and storage of captured video, and prompts a reexamination of traditional routines used to process data in neuroscience and now demand improvements in both our hardware and software applications for processing, analyzing, and storing captured video. This project demonstrates the ease with which a dependable and affordable wide-field fluorescence imaging system can be assembled and integrated with behavior control and monitoring system such as found in a typical neuroscience laboratory. An Open-source MATLAB toolbox is employed to efficiently analyze and visualize large imaging data sets in a manner that is both interactive and fully automated. This software package provides a library of image pre-processing routines optimized for batch-processing of continuous functional fluorescence video, and additionally automates a fast unsupervised ROI detection and signal extraction routine. Further, an extension of this toolbox that uses GPU programming to process streaming video, enabling the identification, segmentation and extraction of neural activity signals on-line is described in which specific algorithms improve signal specificity and image quality at the single cell level in a behaving animal. This project describes the strategic ingredients for transforming a large bulk flow of raw continuous video into proportionally informative images and knowledge

Visual Surveillance and Biometrics: Practices, Challenges, and Possibilities

Visual surveillance is the latest paradigm for social security through machine intelligence. It includes the use of visual data captured by infrared sensors or visible-light cameras mounted in cars, corridors, traffic signals etc. Visual surveillance facilitates the classification of human behavior, crowd activity, and gesture analysis to achieve application-specific objectivesinfo:eu-repo/semantics/publishedVersio

Minds Online: The Interface between Web Science, Cognitive Science, and the Philosophy of Mind

Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis they place on forces and factors that reside at the level of agent–world interactions. In particular, by adopting a situated or ecological approach to cognition, we are able to assess the significance of the Web from the perspective of research into embodied, extended, embedded, social and collective cognition. The results of this analysis help to reshape the interdisciplinary configuration of Web Science, expanding its theoretical and empirical remit to include the disciplines of both cognitive science and the philosophy of mind

EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing

We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments

Visual Attention in Dynamic Environments and its Application to Playing Online Games

Abstract In this thesis we present a prototype of Cognitive Programs (CPs) - an executive controller built on top of Selective Tuning (ST) model of attention. CPs enable top-down control of visual system and interaction between the low-level vision and higher-level task demands. Abstract We implement a subset of CPs for playing online video games in real time using only visual input. Two commercial closed-source games - Canabalt and Robot Unicorn Attack - are used for evaluation. Their simple gameplay and minimal controls put the emphasis on reaction speed and attention over planning. Abstract Our implementation of Cognitive Programs plays both games at human expert level, which experimentally proves the validity of the concept. Additionally we resolved multiple theoretical and engineering issues, e.g. extending the CPs to dynamic environments, finding suitable data structures for describing the task and information flow within the network and determining the correct timing for each process

Gaze-grasp coordination in obstacle avoidance: differences between binocular and monocular viewing

Most adults can skillfully avoid potential obstacles when acting in everyday cluttered scenes. We examined how gaze and hand movements are normally coordinated for obstacle avoidance and whether these are altered when binocular depth information is unavailable. Visual fixations and hand movement kinematics were simultaneously recorded, while 13 right-handed subjects reached-to-precision grasp a cylindrical household object presented alone or with a potential obstacle (wine glass) located to its left (thumb's grasp side), right or just behind it (both closer to the finger's grasp side) using binocular or monocular vision. Gaze and hand movement strategies differed significantly by view and obstacle location. With binocular vision, initial fixations were near the target's centre of mass (COM) around the time of hand movement onset, but usually shifted to end just above the thumb's grasp site at initial object contact, this mainly being made by the thumb, consistent with selecting this digit for guiding the grasp. This strategy was associated with faster binocular hand movements and improved end-point grip precision across all trials than with monocular viewing, during which subjects usually continued to fixate the target closer to its COM despite a similar prevalence of thumb-first contacts. While subjects looked directly at the obstacle at each location on a minority of trials and their overall fixations on the target were somewhat biased towards the grasp side nearest to it, these gaze behaviours were particularly marked on monocular vision-obstacle behind trials which also commonly ended in finger-first contact. Subjects avoided colliding with the wine glass under both views when on the right (finger side) of the workspace by producing slower and straighter reaches, with this and the behind obstacle location also resulting in 'safer' (i.e. narrower) peak grip apertures and longer deceleration times than when the goal object was alone or the obstacle was on its thumb side. But monocular reach paths were more variable and deceleration times were selectively prolonged on finger-side and behind obstacle trials, with this latter condition further resulting in selectively increased grip closure times and corrections. Binocular vision thus provided added advantages for collision avoidance, known to require intact dorsal cortical stream processing mechanisms, particularly when the target of the grasp and potential obstacle to it were fairly closely separated in depth. Different accounts of the altered monocular gaze behaviour converged on the conclusion that additional perceptual and/or attentional resources are likely engaged compared to when continuous binocular depth information is available. Implications for people lacking binocular stereopsis are briefly considered

Development and Application of Semi-automated ITK Tools Development and Application of Semi-automated ITK Tools for the Segmentation of Brain MR Images

Image segmentation is a process to identify regions of interest from digital images. Image segmentation plays an important role in medical image processing which enables a variety of clinical applications. It is also a tool to facilitate the detection of abnormalities such as cancerous lesions in the brain. Although numerous efforts in recent years have advanced this technique, no single approach solves the problem of segmentation for the large variety of image modalities existing today. Consequently, brain MRI segmentation remains a challenging task. The purpose of this thesis is to demonstrate brain MRI segmentation for delineation of tumors, ventricles and other anatomical structures using Insight Segmentation and Registration Toolkit (ITK) routines as the foundation. ITK is an open-source software system to support the Visible Human Project. Visible Human Project is the creation of complete, anatomically detailed, three-dimensional representations of the normal male and female human bodies. Currently under active development, ITK employs leading-edge segmentation and registration algorithms in two, three, and more dimensions. A goal of this thesis is to implement those algorithms to facilitate brain segmentation for a brain cancer research scientist

Army-NASA aircrew/aircraft integration program (A3I) software detailed design document, phase 3

The capabilities and design approach of the MIDAS (Man-machine Integration Design and Analysis System) computer-aided engineering (CAE) workstation under development by the Army-NASA Aircrew/Aircraft Integration Program is detailed. This workstation uses graphic, symbolic, and numeric prototyping tools and human performance models as part of an integrated design/analysis environment for crewstation human engineering. Developed incrementally, the requirements and design for Phase 3 (Dec. 1987 to Jun. 1989) are described. Software tools/models developed or significantly modified during this phase included: an interactive 3-D graphic cockpit design editor; multiple-perspective graphic views to observe simulation scenarios; symbolic methods to model the mission decomposition, equipment functions, pilot tasking and loading, as well as control the simulation; a 3-D dynamic anthropometric model; an intermachine communications package; and a training assessment component. These components were successfully used during Phase 3 to demonstrate the complex interactions and human engineering findings involved with a proposed cockpit communications design change in a simulated AH-64A Apache helicopter/mission that maps to empirical data from a similar study and AH-1 Cobra flight test

Keeping an eye on noisy movements: On different approaches to perceptual-motor skill research and training

Contemporary theorising on the complementary nature of perception and action in expert performance has led to the emergence of different emphases in studying movement coordination and gaze behaviour. On the one hand, coordination research has examined the role that variability plays in movement control, evidencing that variability facilitates individualised adaptations during both learning and performance. On the other hand, and at odds with this principle, the majority of gaze behaviour studies have tended to average data over participants and trials, proposing the importance of universal 'optimal' gaze patterns in a given task, for all performers, irrespective of stage of learning. In this article, new lines of inquiry are considered with the aim of reconciling these two distinct approaches. The role that inter- and intra-individual variability may play in gaze behaviours is considered, before suggesting directions for future research

Knowledge sharing as spontaneous order : on the emergence of strong and weak ties

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