title: Curriculum integration as treaty praxis.

authors: Fraser, Deborah

subjects: curricula

abstract: The article discusses the significance of curriculum integration on the promotion of principles of the Treaty of Waitangi, an agreement signed in 1840 by the Maori and the Crown people in New Zealand. It explores the challenges linked with this curriculum theory design. It also highlights a case study which analyzes the impact of curriculum integration in education.

text: Curriculum integration as treaty praxis. The article discusses the significance of curriculum integration on the promotion of principles of the Treaty of Waitangi, an agreement signed in 1840 by the Maori and the Crown people in New Zealand. It explores the challenges linked with this curriculum theory design. It also highlights a case study which analyzes the impact of curriculum integration in education.

year: 2002

title: Iarararararī

authors: Maxwell, Te Kahautu

abstract: Poi. Lyrics composed by Raniera Poihipi rāua ko Te Kahautu Maxwell. Musical score composed by Te Kahautu Maxwell, Pixie Rogers, Tama Hata, Raharuha Mitai, Renee Mitai, Maisey Rika, Ramari Sherman, Te Rina Ransfield. Performed by Ōpōtiki Mai Tawhiti (Kapa Haka group) (4mins)

Waiata Tira: Aroha
Whakaeke: Haere mai rā
Mōteatea: Te Pātere a Te Turuki
Poi: Iarararararī
Waiata ā ringa: Taku Mana Māori Motuhake
Haka: Waiwharangi
Whakawātea: Āio

text: Iarararararī Poi. Lyrics composed by Raniera Poihipi rāua ko Te Kahautu Maxwell. Musical score composed by Te Kahautu Maxwell, Pixie Rogers, Tama Hata, Raharuha Mitai, Renee Mitai, Maisey Rika, Ramari Sherman, Te Rina Ransfield. Performed by Ōpōtiki Mai Tawhiti (Kapa Haka group) (4mins)

Waiata Tira: Aroha
Whakaeke: Haere mai rā
Mōteatea: Te Pātere a Te Turuki
Poi: Iarararararī
Waiata ā ringa: Taku Mana Māori Motuhake
Haka: Waiwharangi
Whakawātea: Āio

year: 2020-02-06

title: Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex

authors: Steyn-Ross, Moira L.

subjects: REM

abstract: Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer's dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

text: Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer's dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

year: 2005