232,189 research outputs found
Dynamic Adaptive Computation: Tuning network states to task requirements
Neural circuits are able to perform computations under very diverse
conditions and requirements. The required computations impose clear constraints
on their fine-tuning: a rapid and maximally informative response to stimuli in
general requires decorrelated baseline neural activity. Such network dynamics
is known as asynchronous-irregular. In contrast, spatio-temporal integration of
information requires maintenance and transfer of stimulus information over
extended time periods. This can be realized at criticality, a phase transition
where correlations, sensitivity and integration time diverge. Being able to
flexibly switch, or even combine the above properties in a task-dependent
manner would present a clear functional advantage. We propose that cortex
operates in a "reverberating regime" because it is particularly favorable for
ready adaptation of computational properties to context and task. This
reverberating regime enables cortical networks to interpolate between the
asynchronous-irregular and the critical state by small changes in effective
synaptic strength or excitation-inhibition ratio. These changes directly adapt
computational properties, including sensitivity, amplification, integration
time and correlation length within the local network. We review recent
converging evidence that cortex in vivo operates in the reverberating regime,
and that various cortical areas have adapted their integration times to
processing requirements. In addition, we propose that neuromodulation enables a
fine-tuning of the network, so that local circuits can either decorrelate or
integrate, and quench or maintain their input depending on task. We argue that
this task-dependent tuning, which we call "dynamic adaptive computation",
presents a central organization principle of cortical networks and discuss
first experimental evidence.Comment: 6 pages + references, 2 figure
The malleable brain: plasticity of neural circuits and behavior: A review from students to students
One of the most intriguing features of the brain is its ability to be malleable, allowing it to adapt continually to changes in the environment. Specific neuronal activity patterns drive long-lasting increases or decreases in the strength of synaptic connections, referred to as long-term potentiation (LTP) and long-term depression (LTD) respectively. Such phenomena have been described in a variety of model organisms, which are used to study molecular, structural, and functional aspects of synaptic plasticity. This review originated from the first International Society for Neurochemistry (ISN) and Journal of Neurochemistry (JNC) Flagship School held in Alpbach, Austria (Sep 2016), and will use its curriculum and discussions as a framework to review some of the current knowledge in the field of synaptic plasticity. First, we describe the role of plasticity during development and the persistent changes of neural circuitry occurring when sensory input is altered during critical developmental stages. We then outline the signaling cascades resulting in the synthesis of new plasticity-related proteins, which ultimately enable sustained changes in synaptic strength. Going beyond the traditional understanding of synaptic plasticity conceptualized by LTP and LTD, we discuss system-wide modifications and recently unveiled homeostatic mechanisms, such as synaptic scaling. Finally, we describe the neural circuits and synaptic plasticity mechanisms driving associative memory and motor learning. Evidence summarized in this review provides a current view of synaptic plasticity in its various forms, offers new insights into the underlying mechanisms and behavioral relevance, and provides directions for future research in the field of synaptic plasticity.Fil: Schaefer, Natascha. University of Wuerzburg; AlemaniaFil: Rotermund, Carola. University of Tuebingen; AlemaniaFil: Blumrich, Eva Maria. Universitat Bremen; AlemaniaFil: Lourenco, Mychael V.. Universidade Federal do Rio de Janeiro; BrasilFil: Joshi, Pooja. Robert Debre Hospital; FranciaFil: Hegemann, Regina U.. University of Otago; Nueva ZelandaFil: Jamwal, Sumit. ISF College of Pharmacy; IndiaFil: Ali, Nilufar. Augusta University; Estados UnidosFil: GarcĂa Romero, Ezra Michelet. Universidad Veracruzana; MĂ©xicoFil: Sharma, Sorabh. Birla Institute of Technology and Science; IndiaFil: Ghosh, Shampa. Indian Council of Medical Research; IndiaFil: Sinha, Jitendra K.. Indian Council of Medical Research; IndiaFil: Loke, Hannah. Hudson Institute of Medical Research; AustraliaFil: Jain, Vishal. Defence Institute of Physiology and Allied Sciences; IndiaFil: Lepeta, Katarzyna. Polish Academy of Sciences; ArgentinaFil: Salamian, Ahmad. Polish Academy of Sciences; ArgentinaFil: Sharma, Mahima. Polish Academy of Sciences; ArgentinaFil: Golpich, Mojtaba. University Kebangsaan Malaysia Medical Centre; MalasiaFil: Nawrotek, Katarzyna. University Of Lodz; ArgentinaFil: Paid, Ramesh K.. Indian Institute of Chemical Biology; IndiaFil: Shahidzadeh, Sheila M.. Syracuse University; Estados UnidosFil: Piermartiri, Tetsade. Universidade Federal de Santa Catarina; BrasilFil: Amini, Elham. University Kebangsaan Malaysia Medical Centre; MalasiaFil: Pastor, VerĂłnica. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Houssay. Instituto de BiologĂa Celular y Neurociencia ; ArgentinaFil: Wilson, Yvette. University of Melbourne; AustraliaFil: Adeniyi, Philip A.. Afe Babalola University; NigeriaFil: Datusalia, Ashok K.. National Brain Research Centre; IndiaFil: Vafadari, Benham. Polish Academy of Sciences; ArgentinaFil: Saini, Vedangana. University of Nebraska; Estados UnidosFil: Suárez Pozos, Edna. Instituto PolitĂ©cnico Nacional; MĂ©xicoFil: Kushwah, Neetu. Defence Institute of Physiology and Allied Sciences; IndiaFil: Fontanet, Paula. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Houssay. Instituto de BiologĂa Celular y Neurociencia ; ArgentinaFil: Turner, Anthony J.. University of Leeds; Reino Unid
Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics
We introduce a dynamic neural algorithm called Dynamic Neural (DN)
SARSA(\lambda) for learning a behavioral sequence from delayed reward.
DN-SARSA(\lambda) combines Dynamic Field Theory models of behavioral sequence
representation, classical reinforcement learning, and a computational
neuroscience model of working memory, called Item and Order working memory,
which serves as an eligibility trace. DN-SARSA(\lambda) is implemented on both
a simulated and real robot that must learn a specific rewarding sequence of
elementary behaviors from exploration. Results show DN-SARSA(\lambda) performs
on the level of the discrete SARSA(\lambda), validating the feasibility of
general reinforcement learning without compromising neural dynamics.Comment: Sohrob Kazerounian, Matthew Luciw are Joint first author
The systemic dimension of operational decision in complex systems work
This paper refers to some of my research findings on Decision Making processes in complex systems work. Starting as a complex cognitive process strongly contextualized in the operating environment, it ends up, in complex systems work, as an equally complex network of actors and systems (human and technological) that are confronted, in real time, with uncertainty , a large amount of information and feedback and with multiple standards and operating procedures...Complex systems work; Operational Decision; Mental Model; Situational awareness; Systemic decision
Organisational Memory and Innovation Across Projects: Integrated Service Provision in Engineering Design Firms
This paper provides an exploration of the dynamics of organisational remembering in firms operating through projects. The paper focuses in particular on the deliberate use of experience accumulated in the past in order to sustain innovation in the provision of services. It relies on the notions of boundary objects and brokers to empirically explore how a common memory crossing occupational and organisational boundaries is built. In so doing, it highlights how a boundary object as memory device in a project environment operates at different levels, i.e. personal, project-specific, organisational-specific and occupational specific, and how it takes different formats to perform its roles at each level. Finally, the paper highlights the role of specific communities, beyond that of specific individuals, as boundary brokers.project development, innovation processes, organisational memory, boundary brokers
Stress: Putting the Brain Back Into Medicine
Throughout the life course stress plays a major role in health and disease. Although it has long been known that the brain orchestrates the many ways that the body responds to these experiences, a gap exists between health care providers who focus from the head up and those who focus on the head down
Erwin Schroedinger, Francis Crick and epigenetic stability
Schroedinger's book 'What is Life?' is widely credited for having played a
crucial role in development of molecular and cellular biology. My essay
revisits the issues raised by this book from the modern perspective of
epigenetics and systems biology. I contrast two classes of potential mechanisms
of epigenetic stability: 'epigenetic templating' and 'systems biology'
approaches, and consider them from the point of view expressed by Schroedinger.
I also discuss how quantum entanglement, a nonclassical feature of quantum
mechanics, can help to address the 'problem of small numbers' that lead
Schroedinger to promote the idea of molecular code-script for explanation of
stability of biological order.Comment: New and improved version of the essay, now published in the online
journal 'Biology Direct'. Contains more expanded discussion on entanglement.
18 pages, 2 figures. The file includes open reviews by E.Koonin, V.Vedral and
E.Karsent
The cognitive neuroscience of visual working memory
Visual working memory allows us to temporarily maintain and manipulate visual information in order to solve a task. The study of the brain mechanisms underlying this function began more than half a century ago, with Scoville and Milner’s (1957) seminal discoveries with amnesic patients. This timely collection of papers brings together diverse perspectives on the cognitive neuroscience of visual working memory from multiple fields that have traditionally been fairly disjointed: human neuroimaging, electrophysiological, behavioural and animal lesion studies, investigating both the developing and the adult brain
The "MIND" Scalable PIM Architecture
MIND (Memory, Intelligence, and Network Device) is an advanced parallel computer architecture for high performance computing and scalable embedded processing. It is a
Processor-in-Memory (PIM) architecture integrating both DRAM bit cells and CMOS logic devices on the same silicon die. MIND is multicore with multiple memory/processor nodes on
each chip and supports global shared memory across systems of MIND components. MIND is distinguished from other PIM architectures in that it incorporates mechanisms for efficient support of a global parallel execution model based on the semantics of message-driven multithreaded split-transaction processing. MIND is designed to operate either in conjunction with other conventional microprocessors or in standalone arrays of like devices. It also incorporates mechanisms for fault tolerance, real time execution, and active power management. This paper describes the major elements and operational methods of the MIND
architecture
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