EP1. Learning Elena Pasquinelli Educa3on, cogni3on, cerveau Cogmaster 2010‐2011
Op3miza3on of educa3on • “Considera3ons on the op3miza3on of educa3onal strategies should take into account knowledge on brain development and learning mechanisms that has been accumulated by neurobiological research over the past decades.” (Singer, in BaKro, Fischer & Léna, 2008, p. 97)
• Pre‐programming and experience: rela2onship between learning, development, evolu2on • Learning all life‐long? • Learning everything? • Prac2cal issues related to plas2city and learning
RELATIONSHIP BETWEEN LEARNING, EVOLUTION, DEVELOPMENT
Deﬁni3on of learning • Learning = modiﬁca3on of stored • “any learning, i.e. the knowledge and of computa3onal programs modiﬁca2on of computa2onal • Which takes place through the programs and of stored modiﬁca3on of the brain knowledge, must occur func3onal architecture through las$ng changes in their • Learning = long‐las3ng change in func$onal the func3onal architecture of the brain architecture.” (Singer, 2008, p. 98)
Deﬁni3on of knowledge • Knowledge is the product • « there is no dichotomy between of biological processes, hard‐ and soXware in the brain. The which determine or way in which brains operate is fully modify the func3onal determined by the integra3ve architecture of the brain proper3es of the individual nerve • Learning is one of these cells and the way in which they are processes interconnected. It is the func3onal architecture, the blueprint of connec3ons and their respec3ve weight, that determines how brains perceive, decide, and act. • … all the knowledge that a brain possesses reside in its func3onal architecture. » (Singer, 2008, p. 98)
Modiﬁca3on of the brain’s func3onal architecture: 3 processes • 3 diﬀerent “altering the integra2ve proper2es of processes are individual neurons… responsible of changing the anatomical connec2vity the paRerns, … speciﬁca3on/ modifying the eﬃcacy of excitatory modiﬁca3on of and/or inhibitory connec2ons. the brain’s …”(Singer, 2008, p. 98) func3onal architecture (and thus, of knowledge “Evolu3on, acquisi3on): Ontogene3c development, And learning.” (Singer, 2008, p. 98)
a. Learning and evolu3on • Evolu3on has selected both learning mechanisms and knowledge contents: – E.g. : “Fire together, wire together” – E. g. : How to evaluate regulari3es, extract rules, associate signals, iden3fy causal rela3ons, reason, associate emo3ons to sensory s3muli – E. g. How to interpret sensory signals • The brain stores knowledge even before making experiences: it’s not a tabula rasa. – Educa2on cannot be considered as the task of ﬁlling a hollow box
b. Learning and development • The brain at birth is s3ll immature: neurons are in place, basic distant connec3ons between neurons are formed, but not the most part of the neurons of the cortex • From birth to the end of puberty, neural circuits are formed and selected – Development includes 3me window, or expects certain s3muli at speciﬁc periods of the life of the animal in order to implement certain func3ons • During development connec3ons are formed and tested (“ﬁre together‐wire together”): those connec3ons, which have a high probability of being ac3vated simultaneously are consolidated, those which have a low probability are discarded. • AXer birth, this networking ac3vity is inﬂuenced by individual experience of the environment and sensory signals
c. Learning (adult) = func3onal modiﬁca3ons of brain’s func3onal architecture • Development and learning cross their paths, but aXer puberty neural circuits and the structural architecture of the brain are (apparently) mostly stabilized • Adult learning: Func3onal modiﬁca3ons – strength of the connec3ons, – eﬃcacy of the connec3ons • are the main mechanisms for the modiﬁca3on of the func3onal architecture of the brain • Learning does not modify the architecture of the brain at a structural level (mostly): • it produces func3onal modiﬁca3ons that aﬀect the strength of the connec3ons between neurons (synapses) = Func2onal plas2city
The role of experience • In addic3on to gene3c mechanisms, the brain is modiﬁed by experience • Both – At the level of epigenesis and development (see eﬀects of depriva3on) – At the level of learning • But with – constraints to what can be learnt: • certain mechanisms protect the brain from adap3ng to any new informa3on coming from the environment
CAN HUMANS LEARN ALL LIFE LONG? ‐ THE CRITICAL PERIODS ‐ THE ROLE OF EXPERIENCE ‐ THE FORMS OF PLASTICITY
Cri3cal (sensi3ve) periods for learning • Cri3cal periods = 3me‐ window opportuni3es • Development of vision – Hubel & Wiesel, 1970: monocular depriva3on reduces the number of cells responding to the ac3vity of the deprived eye – monocular depriva3on has diﬀerent eﬀects at diﬀerent ages • Development of language
The myth of the ﬁrst three years • The no3on of cri3cal periods has been domina3ng the world of educa3on and has given birth to myth of the ﬁrst three years • Bruer, 1997 describes this myth as a typical case of bad transla3on from neuroscien3ﬁc data to educa3onal applica3ons • Bruer, 1997 cri3cizes the iden3ﬁca3on of learning with synaptogenesis: – Diﬀerent systems have diﬀerent sensi3ve periods, in the sense that they do not develop at the same rate (including within the visual system) – Human cri3cal periods are not necessarily the same as animals – The brain is more plas2c than accorded before – Learning cannot be reduced to synaptogenesis
general rule for neuroeduca3on • Bruer has used the myth of the ﬁrst three years for showing that neuroscience is s3ll a bridge too far from educa3on, and can give rise to neuromyths and misapplica3ons. So pay aKen3on to: • generaliza3on of considera3ons that are extracted from – Animal experiments – Data on speciﬁc func3ons • erroneous iden3ﬁca3on of brain mechanism and behavioral phenomenon – E.g., Iden3ﬁca3on of learning with synaptogenesis
From cri3cal periods to diﬀerent forms of plas3city • (Greenough, Black & Wallace, 1987) have introduced the dis3nc3on between two ways in which experience modiﬁes the brain: • Experience‐expectant plas2city: – Selected by evolu3on – Concerns sensory motor func3ons – Allows to ﬁne‐tune the sensory motor systems in rela3onship to the environment – Through the selec2on of synapses that have been generated in excess – Deﬁnes the s3muli that should be found in the environment for the func3on to develop in a certain way – Experiences are very general and concern s3muli, which are normally present in the environment • Experience‐dependent plas2city: – Does not depend on mechanisms that have been selected by evolu3on according to a precise 3ming – Evolu3on has selected a capacity to learn from experience in general – Through the genera2on of synapses, and the modiﬁca2on of the strength of the synapses
3 mechanisms for func3onal and structural plas3city • Plas3city is the basis of learning from • « The most fascina3ng and important experience property of mammalian brain is its • 3 mechanisms: remarkable plas3city, which can be – Synap3c plas3city = change in strength thought of as the ability of or eﬃcacy of synap3c transmission experience to modify neural circuitry – Synaptogenesis & synap3c pruning and thereby to modify future – Excitability proper3es of single neurons thought, behavior, feeling.» (Malenka, 2002, p. 147) • Synap3c plas3city can be transient (short term phenomena such as short‐term adapta3on to sensory inputs) – depends on modula3on of transmiKer release • Or long las3ng: long‐term form of memory – LTP/LTD (long‐term poten3a3on/long‐ term depression) mechanisms
LTP • LTP: repe33ve ac3va3on of excitatory synapses in the hyppocampus causes an increase in synap3c strength that can last for hours • LTP is hypothesized to be involved in the forma3on of memories and more generally in informa3on storing, hence in learning in general, because LTP and learning considered at the behavioral level share some proper3es: – LTP can be generated rapidly and is prolonged and strengthened by repe33on – It is input speciﬁc (it is elicited at the ac3vated synapses and not at adjacent synapses of the same neuron) – It’s long‐las3ng • How? Modiﬁca3on of dendri3c spines? Growth of spines? Genera3on of new synapses as a consequence of the splinng or duplica3on of exis3ng spines? • Incorpora3ng structural changes into the mechanisms of long‐term synap3c plas3city provides means by which the ac3vity generated by experience can cause long‐las3ng modiﬁca3ons of neural circuitry
More “structural” plas3city • “ Un3l rela3vely recently, it was widely assumed that, except for certain cases of response to brain damage, the brain acquired all of the synapses it was going to have during development, and that further plas3c change was probably accomplished through modiﬁca3ons of the strength of preexis3ng connec3ons. • … it has now become quite clear that new connec3ons may arise as a result of diﬀeren3al housing condi3ons and other manipula3ons throughout much, if not all, the life of the rat… • There has not yet been a speciﬁc demonstra3on of what might be represented by the changes in synap3c connec3ons brought about by diﬀeren3al environmental complexity, nor are the details of the rela3onship between brain structure and behavioral performance.” (Greenough, Black & Wallace, 1987, p. 547‐548) • “However, there are a few excep3ons. Over the past years, evidence has become available that in a few dis3nct brain region, parts of the hippocampus and the olfactory bulb neurons con3nue to be generated throughout life, and these neurons form new connec3ons and become integrated in exis3ng circuitry.” • “Thus in these dis3nct areas of the brain, developmental processes persist throughout life…” (Singer, 2008, p. 108)
Structural plas3city in the adult brain • MRI of licensed London taxi drivers were analyzed and compared with those of control subjects who did not drive taxis. • The posterior hippocampi of taxi drivers were signiﬁcantly larger rela3ve to those of control subjects. • Hippocampal volume correlated with the amount of 3me spent as a taxi driver (posi3vely in the posterior and nega3vely in the anterior hippocampus). • These data are in accordance with the idea that the posterior hippocampus stores a spa3al representa3on of the environment and can expand regionally to accommodate elabora3on of this representa3on in people with a high dependence on naviga3onal skills. • It seems that there is a capacity for local plas3c change in the structure of the healthy adult human brain in response to environmental demands. (Maguire, et al.,2000)
CAN HUMANS LEARN ANYTHING? ‐ BIOLOGICAL CONSTRAINTS ‐ THE ROLE OF EDUCATION
The role of educa3on • 3 possible views: – One can learn everything, and learns it from scratch – What we learn depends on past experiences and is constructed star3ng from these experiences, but one can learn everything – The way brain has been shaped by selec3on strongly constrains what can be learnt • (Posner & Rothbart, 2007)
Can we learn anything? Constraints and biases • Learning experiences sculpt the brain and cons3tute a framework for future learning • E. g. According to Kuhl (2004) mother language learning builds a mental ﬁlter that limits second language learning • the “cri3cal period” depends on experience as much as 3me, and is a process rather than a strictly 3med window of opportunity that is opened and closed by matura3on. – (Bransford, et al, in Sawyer, 2009)
Can we learn anything? Evolu3on and selec3on • «… I have oXen observed that educators hold an implicit model of brain as a tabula rasa or blank slate (Pinker, 2002), ready to be ﬁlled through educa3on and classroom prac3ce. In this view, the capacity of the human brain to be educated, unique in the human kingdom, relies upon an extended range of cor3cal plas3city unique to humans. The human brain would be special in its capacity to accommodate an almost inﬁnite range of new func3ons through learning. • In this view, then, knowledge of the brain is of no help in designing educa3onal policies. • …. Much of current classroom content, so the reasoning goes, consists in recent cultural inven3ons, such as the symbols we use in wri3ng or mathema3cs. Those cultural tools are far too recent to have exerted any evolu3onary pressure on brain evolu3on. … Thus, it is logically impossible that there exist dedicated brain mechanisms evolved for reading or symbolic arithme3c. They have to be learned, just like myriads of other facts and skills in geography, history, grammar, philosophy … The fact that our children can learn those materials implies that the brain is nothing but a powerful universal learning machine. » (Dehaene, in BaKro, Fischer, & Léna, 2008, p. 233).
Biology and culture • Implica3on of the idea of tabula rasa: each learner is radically diﬀerent from other learners, and the same cerebral areas can be aﬀected to diﬀerent func3ons
Neural recycling hypothesis • “… Close examina3on of the func3ons of those brain areas in evolu3on suggests a possible resolu3on of this paradox. It is not the case that those areas acquire an en3rely dis3nct, culturally arbitrary new func3on. Rather, they appear to possess, in other primates, a prior func3on closely related to the one that they will eventually have in humans. … rela3vely small changes may suﬃce to adapt them to their new cultural domain. • « neural recycling hypothesis », according to which the human capacity for cultural learning relies on a process of pre‐emp3ng or recycling pre‐exis3ng brain circuitry. • In my opinion, this view implies that an understanding of the child’s brain organiza3on is essen3al to educa3on.
Neural recycling & mathema3cs • Arabic digits and verbal numerals are culturally arbitrary and speciﬁc to humans • the sense of numerical quan3ty is not: it is present in infants and animals • We learn to give meaning to our symbols and calcula3on by connec3ng them to this pre‐exis3ng quan3ty representa3on
Neural recycling & reading • Visual cortex presents mechanisms for invariant shape recogni3on • Visual cortex is connected with auditory and seman3c areas • Visual cortex responds to T shapes, circles, superposed circles.. • Many of these shapes resemble to our leKers • We do not need to create a reading area ex novo, but can preempt other visual and auditory mechanisms
PRACTICAL ISSUES RELATED TO PLASTICITY AND LEARNING ‐ LONG‐LASTING LEARNING ‐ TRANSFERABLE LEARNING ‐ REAL LEARNING EFFECT
From theory to prac3ce • How can we generate successful interven3ons for promo3ng relevant learning ? – How do we pass from theory to prac3ce? – Which kind of theory and evidence do we need? – What is relevant learning? – Learning that is long‐las3ng and transferable – How do we promote learning that is long‐las2ng and transferable?
Plas3city in prac3ce • “Learning and brain plas3city are fundamental proper3es of the nervous system, and they hold considerable promise when it comes to learning a second language faster, maintaining our perceptual and cogni3ve skills as we age, or recovering lost func3ons aXer brain injury. • Learning is cri3cally dependent on experience and the environment that the learner has to face. • … we are s2ll missing the recipe for successful brain plas2city interven2on at the prac2cal level.” (Bavelier, et al., in Gazzaniga, 2009, p. 153)
Training & Relevant learning • In many cases, training produces eﬀects that cannot be considered as relevant learning, because (Bavelier, et al., in Gazzaniga, 2009, p. 153): – They are not long‐las2ng : an eﬀect on learning is not proved by experiments that evaluate short‐ term eﬀects (e.g.: violent eﬀects of violent video games) – They are not suﬃciently generalized: an eﬀect on learning that is bound to the trained task is barely interes3ng – Other variables than the learning experience produce an eﬀect, but are not controlled for and evaluated
Learning as reusable • “Learning involves acquiring new informa3on • Learning is supposed to be re‐usable and u2lizing it later when necessary. Thus, – An example: Imagine a motor therapy which any kind of learning implies generaliza2on of induces the learning of new movements, but the originally acquired informa3on: to new these movements can only be accomplished occasions, new loca3ons, new objects, new in the therapy room contexts, etc. However, any piece of new informa3on that an organism perceives is episodic and par3cular: it involves a single 3me, a speciﬁc loca3on and context, and par3cular objects).” (Gergely & Csibra, 2009, p. 3) • “The ques3on of how one can learn (i.e., acquire general knowledge) from bits of episodic informa3on is known as the induc2on problem and has been tackled by various theories of learning. These usually rely on sta3s3cal procedures that involve sampling mul3ple episodes of experience to form the basis of generaliza3on to novel instances.” (Gergely & Csibra, p. 3)
The neuromyth of the Mozart eﬀect • The Mozart eﬀect (Rauscher, Shaw, Ky, 1993) – Eﬀects of listening music on spa3al reasoning (Stanford‐ Binet IQ test) – Enhancement – For 15 minutes • a classic case of performance enhancement that is NOT a form of learning, because it does not last • … and a classic neuromyth – listening to Mozart increases the IQ
Georgias Governor Seeks Musical Start for Babies, By KEVIN SACK Published: January 15, 1998 ATLANTA, Jan. 14 — As it is, newborn children in Georgia oXen come home from the hospital with a bag of free goodies: baby wipes, diapers, instruc3ons about breast feeding and immuniza3ons. Now Gov. Zell Miller wants to throw in a liKle something extra: a casseKe tape or compact disc of classical music. The music would not be intended to soothe the frayed nerves of parents genng their ﬁrst doses of sleep‐depriva3on from their colicky babies. Rather, Mr. Miller, a devoted fan of country and bluegrass music, is convinced that Bach and Mozart can s3mulate brain development at very early ages. That is why Mr. Miller, a Democrat, proposed as part of his $12.5 billion state budget on Tuesday to spend $105,000 to make music available to each of the approximately 100,000 children born in Georgia each year. No one ques3ons that listening to music at a very early age aﬀects the spa3al, temporal reasoning that underlies math and engineering and even chess, the Governor said today. Having that infant listen to soothing music helps those trillions of brain connec3ons to develop.
Aggression and violent video games • Violent video games seem to produce eﬀects on physiological arousal, verbal violence, but these eﬀects are only tested few minutes aXer the exposi3on (Bavelier, et al., in Gazzaniga, 2009, p. 154)
Transfer • “In the ﬁeld of learning, transfer of learning from the trained task to even other very similar task is generally the excep3on rather than the rule. • For instance, Pashler and Baylis (1991) trained subjects to associate one of three keys with visually presented symbols (leX key = P or 2, middle key = V or 8, right key = K or 7). Over the course of mul3ple training blocks, par3cipants reac3on 3me decreased signiﬁcantly. However, when new symbols were added that needed to be mapped to the same keys in addic3on to the learned symbols … no evidence of transfer was evident.” (Bavelier, et al., in Gazzaniga, 2009, p. 153‐154)
Methodological issues • Studies on the eﬀects of training on learning should prove that the eﬀects are long‐las3ng and that there is a causal rela3onship between the kind of training and the learning eﬀect (Bavelier, et al., in Gazzaniga, 2009, p. 154‐155) – The Hawthorne eﬀect of learning: mo3va3onal factors inﬂuence performance, but they are not part of the learning experience being evaluated – The popula3on eﬀect: causal links are not the same than correla3ons, since correla3on could depend from external factors
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