Young students struggle with concepts that involve the parallel activity of large numbers of similar entities, precisely the kind of concepts that abound in neuroscience. While a direct experience to laboratory work cannot be replaced, such activities include a steep learning curve and may be impractical in certain course settings. This article describes a set of computer simulations of a number of neural processes using NetLogo (Wilensky, 1999), a software environment for the design and implementation of multi-agent simulations that has an intuitive graphical interface and minimal learning curve. NeuroLab is a group of graphical simulations that portray ions, molecules, synapses or cells as individual recognizable agents with particular behaviors, depending on the level at which the particular process is simulated. On a typical assignment, students run the simulation a few times manipulating specific variables by means of buttons, switches and sliders and observe the results of their manipulations on the main window. Many simulations include one or more plots that help visualize statistical data in real time and allow for the testing of experimental hypotheses. Students may repeat the simulation as many times as they wish and collect data or answer questions based on their observations. Assignments may take just a few minutes to perform...
NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API...
Clinical psychology is starting to explain eating disorders (ED) as the outcome of the interaction among cognitive, socio-emotional and interpersonal elements. In particular two influential models—the revised cognitive-interpersonal maintenance model and the transdiagnostic cognitive behavioral theory—identified possible key predisposing and maintaining factors. These models, even if very influential and able to provide clear suggestions for therapy, still are not able to provide answers to several critical questions: why do not all the individuals with obsessive compulsive features, anxious avoidance or with a dysfunctional scheme for self-evaluation develop an ED? What is the role of the body experience in the etiology of these disorders? In this paper we suggest that the path to a meaningful answer requires the integration of these models with the recent outcomes of cognitive neuroscience. First, our bodily representations are not just a way to map an external space but the main tool we use to generate meaning, organize our experience, and shape our social identity. In particular, we will argue that our bodily experience evolves over time by integrating six different representations of the body characterized by specific pathologies—body schema (phantom limb)...
Behavioral studies have shown that human cognition is characterized by properties such as temporal scale invariance, heavy-tailed non-Gaussian distributions, and long-range correlations at long time scales, suggesting models of how (non observable) components of cognition interact. On the other hand, results from functional neuroimaging studies show that complex scaling and intermittency may be generic spatio-temporal properties of the brain at rest. Somehow surprisingly, though, hardly ever have the neural correlates of cognition been studied at time scales comparable to those at which cognition shows scaling properties. Here, we analyze the meanings of scaling properties and the significance of their task-related modulations for cognitive neuroscience. It is proposed that cognitive processes can be framed in terms of complex generic properties of brain activity at rest and, ultimately, of functional equations, limiting distributions, symmetries, and possibly universality classes characterizing them.
Three widespread assumptions of Cognitive-affective Neuroscience are discussed: first, mental functions are assumed to be localized in circumscribed brain areas which can be exactly determined, at least in principle (localizationism). Second, this assumption is associated with the more general claim that these functions (and dysfunctions, such as in neurological or mental diseases) are somehow generated inside the brain (internalism). Third, these functions are seen to be “biological” in the sense that they can be decomposed and finally explained on the basis of elementary biological causes (i.e., genetic, molecular, neurophysiological etc.), causes that can be identified by experimental methods as the gold standard (isolationism). Clinical neuropsychology is widely assumed to support these tenets. However, by making reference to the ideas of Kurt Goldstein (1878–1965), one of its most important founders, I argue that none of these assumptions is sufficiently supported. From the perspective of a clinical-neuropsychological practitioner, assessing and treating brain damage sequelae reveals a quite different picture of the brain as well as of us “brain carriers”, making the organism (or person) in its specific environment the crucial reference point. This conclusion can be further elaborated: all experimental and clinical research on humans presupposes the notion of a situated...
It is becoming ever more accepted that investigations of mind span the brain, body, and environment. To broaden the scope of what is relevant in such investigations is to increase the amount of data scientists must reckon with. Thus, a major challenge facing scientists who study the mind is how to make big data intelligible both within and between fields. One way to face this challenge is to structure the data within a framework and to make it intelligible by means of a common theory. Radical embodied cognitive neuroscience can function as such a framework, with dynamical systems theory as its methodology, and self-organized criticality as its theory.
Students who engage in experiential research programs and who form communities of learning are more likely to persist in Science, Technology, Engineering, and Math (STEM) programs. Faculty who collaborate are more likely to publish and to stay engaged in their field. With funding from the Great Lakes Colleges Association (GLCA) Expanding Collaboration Initiative, we engaged in a series of summer seminars with neuroscience faculty and their research students at five regional institutions, the College of Wooster, Ohio Wesleyan University, Earlham College, Oberlin College and Kenyon College. Our goals were to provide an opportunity for faculty and students to learn about the methods used in the labs at these institutions, to increase collaborative relationships across these institutions, to develop a community of learning among participating students, and to provide students with professional development opportunities. Pre- and post-assessment data indicate knowledge gains in demonstrated methods and increased comfort performing the methods with supervision or collaboration. In addition, several collaborative relationships were formed and significant assistance with planning, materials, and/or apparatus was provided across institutions. In open-ended post-experience questions...
The significance of early and sporadic reports in the 19th century of impairments of motion vision following brain damage was largely unrecognized. In the absence of satisfactory post-mortem evidence, impairments were interpreted as the consequence of a more general disturbance resulting from brain damage, the location and extent of which was unknown. Moreover, evidence that movement constituted a special visual perception and may be selectively spared was similarly dismissed. Such skepticism derived from a reluctance to acknowledge that the neural substrates of visual perception may not be confined to primary visual cortex. This view did not persist. First, it was realized that visual movement perception does not depend simply on the analysis of spatial displacements and temporal intervals, but represents a specific visual movement sensation. Second persuasive evidence for functional specialization in extrastriate cortex, and notably the discovery of cortical area V5/MT, suggested a separate region specialized for motion processing. Shortly thereafter the remarkable case of patient LM was published, providing compelling evidence for a selective and specific loss of movement vision. The case is reviewed here, along with an assessment of its contribution to visual neuroscience.
Collaborations between neuroscience and music therapy promise many mutual benefits given the different knowledge bases, experiences and specialist skills possessed by each discipline. Primarily, music therapists deliver music-based interventions on a daily basis with numerous populations; neuroscientists measure clinical changes in ways that provide an evidence base for progressing clinical care. Although recent developments suggest that partnerships between the two can produce positive outcomes for both fields, these collaborations are not considered mainstream. The following dialog between an experienced professional from each discipline explores the potential for collaboration, as well as the misconceptions that may be preventing further synergies from developing.
ERIN, Educational Resources in Neuroscience, is the Society for Neuroscience’s web portal to selected, high-quality materials for higher education. A Board of Editors approves resources after describing them and classifying them by topic, subtopic, media type, author, and appropriate educational level. Some resources are also accompanied by reviews and ratings from faculty who have used the resource. These features make a search of ERIN far more useful than a typical Google search.
Academia has recently been under mounting pressure to increase accountability and intentionality in instruction through development of student “intended learning outcomes” (ILOs) developed at multiple levels (e.g., course, program, major, and even institution). Once these learning goals have been determined, then classroom instruction can be purposefully designed to map onto those intended outcomes in a “backward design” process (Wiggins and McTighe, 2005). The ongoing challenge with any such process, however, is in determining one’s effectiveness in achieving these intended learning goals, so it is critical that efficient tools can be developed that enable these goals to be assessed. In addition, an important requirement of any ILOs is that they are mission-driven, meaningful and parsed in such a way that they can be used to obtain evidence in a manageable way. So how can we effectively assess these outcomes in our students? This paper describes key factors to consider in the planning and implementation of assessment for an undergraduate neuroscience program.
Recent advances in optical and electron microscopy allow scientists to acquire extremely high-resolution images for neuroscience research. Datasets imaged with modern electron microscopes can range between tens of terabytes to about one petabyte in size. These large data sizes and the high complexity of the underlying neural structures make it very challenging to handle the data at reasonably interactive rates. To provide neuroscientists flexible and interactive tools for their scientific work we introduce SSECRETT and NeuroTrace, two systems that were designed for interactive exploration and analysis of large-scale optical and electron microscope images to reconstruct complex neural circuits of the mammalian nervous system.; Engineering and Applied Sciences
We used functional magnetic resonance imaging to investigate how the human brain processes information about social groups in three domains. Study 1: Semantic knowledge. Participants were scanned while they answered questions about their knowledge of both social categories and non-social categories like object groups and species of nonhuman animals. Brain regions previously identified in processing semantic information are more robustly engaged by nonsocial semantics than stereotypes. In contrast, stereotypes elicit greater activity in brain regions implicated in social cognition. These results suggest that stereotypes should be considered distinct from other forms of semantic knowledge. Study 2: Theory of mind. Participants were scanned while they answered questions about the mental states and physical attributes of individual people and groups. Regions previously associated with mentalizing about individuals were also robustly responsive to judgments of groups. However, multivariate searchlight analysis revealed that several of these regions showed distinct multivoxel patterns of response to groups and individual people. These findings suggest that perceivers mentalize about groups in a manner qualitatively similar to mentalizing about individual people...
Fonte: Universidade RicePublicador: Universidade Rice
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
The advance of web-based technology has stimulated
innovation in education. This paper discusses the
development and evaluation of an online multimedia
resource for undergraduate-level behavioral neuroscience
education. This resource surveys four major subject areas:
language, attention and perception, thinking, and autism. It
employs audio and video streaming, online demonstration
experiments, computer simulation, and internet links. This
online resource has two distinct advantages over a paper
textbook. First, a considerable proportion of the content is
conveyed using multimedia, thus making the learning
experience more vivid and dynamic. Second, its
interactive components provide opportunities for students
to participate in the various experimental tasks introduced
in the text and to compare their own performance with
those of others. This hands-on experience not only
enables students to gain in-depth procedural knowledge of
the tasks but also has positive effects on their motivation.
Feedback from three undergraduate classes that used this
resource as supplementary material showed that students
were highly positive about its pedagogical values. This
free resource is available on the web at
A hallucination is a distortion of sensory perception with the same qualities of a real perception, but without external stimulation of a sensory organ. It is estimated that approximately 60% to 70% of patients with this disorder and other psychopathology and to have symptoms, despite its strong association with schizophrenia, many studies have shown that auditory hallucinations can also be measured in non-psychiatric population with rates many times greater than all psychotic disorders combined. Neuroimaging technologies have been widely used in an attempt to understand the brain regions and circuits involved in the genesis of hallucinations, and patients with schizophrenia has been studied more frequently. This article aims to review the literature on neuroscience have helped in the process of discovery processes involving auditory hallucinations. It is concluded that neuroimaging data have confirmed the expectation that the hallucinations involve changes in the activity of neural circuits known to be involved in normal hearing liguagem and its control, but the big question of how this altered activity arises, remains unanswered.; A alucinação é uma distorção da percepção sensorial com as mesmas qualidades de uma percepção real...
Successful human social interaction depends on our capacity to understand other people's mental states and to anticipate how they will react to our actions. Despite its importance to the human condition, the exact mechanisms underlying our ability to understand another's actions, feelings, and thoughts are still a matter of conjecture. Here, we consider this problem from philosophical, psychological, and neuroscientific perspectives. In a critical review, we demonstrate that attempts to draw parallels across these complementary disciplines is premature: The second-person perspective does not map directly to Interaction or Simulation theories, online social cognition, or shared neural network accounts underlying action observation or empathy. Nor does the third-person perspective map onto Theory-Theory (TT), offline social cognition, or the neural networks that support Theory of Mind (ToM). Moreover, we argue that important qualities of social interaction emerge through the reciprocal interplay of two independent agents whose unpredictable behavior requires that models of their partner's internal state be continually updated. This analysis draws attention to the need for paradigms in social neuroscience that allow two individuals to interact in a spontaneous and natural manner and to adapt their behavior and cognitions in a response contingent fashion due to the inherent unpredictability in another person's behavior. Even if such paradigms were implemented...
Physiological measurements in neuroscience experiments often involve complex stimulus paradigms and multiple data channels. Ephus (http://www.ephus.org) is an open-source software package designed for general-purpose data acquisition and instrument control. Ephus operates as a collection of modular programs, including an ephys program for standard whole-cell recording with single or multiple electrodes in typical electrophysiological experiments, and a mapper program for synaptic circuit mapping experiments involving laser scanning photostimulation based on glutamate uncaging or channelrhodopsin-2 excitation. Custom user functions allow user-extensibility at multiple levels, including on-line analysis and closed-loop experiments, where experimental parameters can be changed based on recently acquired data, such as during in vivo behavioral experiments. Ephus is compatible with a variety of data acquisition and imaging hardware. This paper describes the main features and modules of Ephus and their use in representative experimental applications.
Posterior cortical atrophy (PCA) is a rare focal neurodegenerative syndrome characterized by progressive visuoperceptual and visuospatial deficits, most often due to atypical Alzheimer's disease (AD). We applied insights from basic visual neuroscience to analyze 3D shape perception in humans affected by PCA. Thirteen PCA patients and 30 matched healthy controls participated, together with two patient control groups with diffuse Lewy body dementia (DLBD) and an amnestic-dominant phenotype of AD, respectively. The hierarchical study design consisted of 3D shape processing for 4 cues (shading, motion, texture, and binocular disparity) with corresponding 2D and elementary feature extraction control conditions. PCA and DLBD exhibited severe 3D shape-processing deficits and AD to a lesser degree. In PCA, deficient 3D shape-from-shading was associated with volume loss in the right posterior inferior temporal cortex. This region coincided with a region of functional activation during 3D shape-from-shading in healthy controls. In PCA patients who performed the same fMRI paradigm, response amplitude during 3D shape-from-shading was reduced in this region. Gray matter volume in this region also correlated with 3D shape-from-shading in AD. 3D shape-from-disparity in PCA was associated with volume loss slightly more anteriorly in posterior inferior temporal cortex as well as in ventral premotor cortex. The findings in right posterior inferior temporal cortex and right premotor cortex are consistent with neurophysiologically based models of the functional anatomy of 3D shape processing. However...
The theory of integrative levels provides a general description of the evolution of matter through successive orders of complexity and integration. Along its development, material forms pass through different levels of organization, such as physical, chemical, biological or sociological. The appearance of novel structures and dynamics during this process of development of matter in complex systems has been called emergence. Social neuroscience (SN), an interdisciplinary field that aims to investigate the biological mechanisms that underlie social structures, processes, and behavior and the influences between social and biological levels of organization, has affirmed the necessity for including social context as an essential element to understand the human behavior. To do this, SN proposes a multilevel integrative approach by means of three principles: multiple determinism, nonadditive determinism and reciprocal determinism. These theoretical principles seem to share the basic tenets of the theory of integrative levels but, in this paper, we aim to reveal the differences among both doctrines. First, SN asserts that combination of neural and social variables can produce emergent phenomena that would not be predictable from a neuroscientific or social psychological analysis alone; SN also suggests that to achieve a complete understanding of social structures we should use an integrative analysis that encompasses levels of organization ranging from the genetic level to the social one; finally...
Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the “predictive brain” are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed in this article. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a “social predictive brain” are also mentioned...