domingo, 20 de enero de 2013

Extreme Weather Rages Worldwide

NY Times
January 10, 2013

Heat, Flood or Icy Cold, Extreme Weather Rages Worldwide

WORCESTER, England — Britons may remember 2012 as the year the weather spun off its rails in a chaotic concoction of drought, deluge and flooding, but the unpredictability of it all turns out to have been all too predictable: Around the world, extreme has become the new commonplace.
Especially lately. China is enduring its coldest winter in nearly 30 years. Brazil is in the grip of a dreadful heat spell. Eastern Russia is so freezing — minus 50 degrees Fahrenheit, and counting — that the traffic lights recently stopped working in the city of Yakutsk.
Bush fires are raging across Australia, fueled by a record-shattering heat wave. Pakistan was inundated by unexpected flooding in September. A vicious storm bringing rain, snow and floods just struck the Middle East. And in the United States, scientists confirmed this week what people could have figured out simply by going outside: last year was the hottest since records began.
“Each year we have extreme weather, but it’s unusual to have so many extreme events around the world at once,” said Omar Baddour, chief of the data management applications division at the World Meteorological Organization, in Geneva. “The heat wave in Australia; the flooding in the U.K., and most recently the flooding and extensive snowstorm in the Middle East — it’s already a big year in terms of extreme weather calamity.”
Such events are increasing in intensity as well as frequency, Mr. Baddour said, a sign that climate change is not just about rising temperatures, but also about intense, unpleasant, anomalous weather of all kinds.
Here in Britain, people are used to thinking of rain as the wallpaper on life’s computer screen — an omnipresent, almost comforting background presence. But even the hardiest citizen was rattled by the near-biblical fierceness of the rains that bucketed down, and the floods that followed, three different times in 2012.
Rescuers plucked people by boat from their swamped homes in St. Asaph, North Wales. Whole areas of the country were cut off when roads and train tracks were inundated at Christmas. In Megavissey, Cornwall, a pub owner closed his business for good after it flooded 11 times in two months.
It was no anomaly: the floods of 2012 followed the floods of 2007 and also the floods of 2009, which all told have resulted in nearly $6.5 billion in insurance payouts. The Met Office, Britain’s weather service, declared 2012 the wettest year in England, and the second-wettest in Britain as a whole, since records began more than 100 years ago. Four of the five wettest years in the last century have come in the past decade (the fifth was in 1954).
The biggest change, said Charles Powell, a spokesman for the Met Office, is the frequency in Britain of “extreme weather events” — defined as rainfall reaching the top 1 percent of the average amount for that time of year. Fifty years ago, such episodes used to happen every 100 days; now they happen every 70 days, he said.
The same thing is true in Australia, where bush fires are raging across Tasmania and the current heat wave has come after two of the country’s wettest years ever. On Tuesday, Sydney experienced its fifth-hottest day since records began in 1910, with the temperature climbing to 108.1 degrees. The first eight days of 2013 were among the 20 hottest on record.
Every decade since the 1950s has been hotter in Australia than the one before, said Mark Stafford Smith, science director of the Climate Adaptation Flagship at the Commonwealth Scientific and Industrial Research Organization.
To the north, the extremes have swung the other way, with a band of cold settling across Russia and Northern Europe, bringing thick snow and howling winds to Stockholm, Helsinki and Moscow. (Incongruously, there were also severe snowstorms in Sicily and southern Italy for the first time since World War II; in December, tornadoes and waterspouts struck the Italian coast.)
In Siberia, thousands of people were left without heat when natural gas liquefied in its pipes and water mains burst. Officials canceled bus transportation between cities for fear that roadside breakdowns could lead to deaths from exposure, and motorists were advised not to venture far afield except in columns of two or three cars. In Altai, to the east, traffic officials warned drivers not to use poor-quality diesel, saying that it could become viscous in the cold and clog fuel lines.
Meanwhile, China is enduring its worst winter in recent memory, with frigid temperatures recorded in Harbin, in the northeast. In the western region of Xinjiang, more than 1,000 houses collapsed under a relentless onslaught of snow, while in Inner Mongolia, 180,000 livestock froze to death. The cold has wreaked havoc with crops, sending the price of vegetables soaring.
Way down in South America, energy analysts say that Brazil may face electricity rationing for the first time since 2002, as a heat wave and a lack of rain deplete the reservoirs for hydroelectric plants. The summer has been punishingly hot. The temperature in Rio de Janeiro climbed to 109.8 degrees on Dec. 26, the city’s highest temperature since official records began in 1915.
At the same time, in the Middle East, Jordan is battling a storm packing torrential rain, snow, hail and floods that are cascading through tunnels, sweeping away cars and spreading misery in Syrian refugee camps. Amman has been virtually paralyzed, with cars abandoned, roads impassable and government offices closed.
Israel and the Palestinian territories are grappling with similar conditions, after a week of intense rain and cold winds ushered in a snowstorm that dumped eight inches in Jerusalem alone.
Amir Givati, head of the surface water department at the Israel Hydrological Service, said the storm was truly unusual because of its duration, its intensity and its breadth. Snow and hail fell not just in the north, but as far south as the desert city of Dimona, best known for its nuclear reactor.
In Beirut on Wednesday night, towering waves crashed against the Corniche, the seaside promenade downtown, flinging water and foam dozens of feet in the air as lightning flickered across the dark sea at multiple points along the horizon. Many roads were flooded as hail pounded the city.
Several people died, including a baby boy in a family of shepherds who was swept out of his mother’s arms by floodwaters. The greatest concern was for the 160,000 Syrian refugees who have fled to Lebanon, taking shelter in schools, sheds and, where possible, with local families. Some refugees are living in farm outbuildings, which are particularly vulnerable to cold and rain.
Barry Lynn, who runs a forecasting business and is a lecturer at the Hebrew University’s department of earth science, said a striking aspect of the whole thing was the severe and prolonged cold in the upper atmosphere, a big-picture shift that indicated the Atlantic Ocean was no longer having the moderating effect on weather in the Middle East and Europe that it has historically.
“The intensity of the cold is unusual,” Mr. Lynn said. “It seems the weather is going to become more intense; there’s going to be more extremes.”
In Britain, where changes to the positioning of the jet stream — a ribbon of air high up in the atmosphere that helps steer weather systems — may be contributing to the topsy-turvy weather, people are still recovering from the December floods. In Worcester last week, the river Severn remained flooded after three weeks, with playing fields buried under water.
In the shop at the Worcester Cathedral, Julie Smith, 54, was struggling, she said, to adjust to the new uncertainty.
“For the past seven or eight years, there’s been a serious incident in a different part of the country,” Mrs. Smith said. “We don’t expect extremes. We don’t expect it to be like this.”
Reporting was contributed by Jodi Rudoren from Jerusalem; Irit Pazner Garshowitz from Tzur Hadassah, Israel; Fares Akram from Gaza City, Gaza; Ellen Barry and Andrew Roth from Moscow; Ranya Kadri from Amman, Jordan; Dan Levin from Harbin, China; Jim Yardley from New Delhi; Anne Barnard from Beirut, Lebanon; Matt Siegel from Sydney, Australia; Scott Sayare from Paris; and Simon Romero from Rio de Janeiro.

Environmental Activism for Academic Credits

For its interest, I paste this message DIRECTLY from  ENVITONMENTAL ANTHROPOLOGY EANTH-L(at)LISTSERV.UGA.EDU...
Just recently I was thinking about the subject; It is a very great idea; as thia opened also a window for academics and their activities in activism, that would be included in curricula 
 ----------      ------------        --------
environmental activism for course credit? 
Hi everyone,

I'm teaching a graduate-level course this coming semester called Environmental
History of the Modern World, which I've taught once before. It deals with a laundry
list of environmental issues - you can imagine. I'm reviewing the readings and films
to be assigned and, as always, getting really upset and frustrated at the world's
environmental problems. So I had an idea. Instead of just assigning essays and
exams, I thought I might have the students do environmental activism projects as one
assignment. This would span the semester, and could take various forms such as
petitioning the university to stop providing bottled water or to divest from oil
companies, or getting involved at the community level, or volunteering for an NGO,
or whatever. I thought they could create a portfolio documenting their efforts, and
the results thereof, which would be what I'd grade at the end.

So I'm wondering if this is just a hare-brained idea, or if anyone else has tried
this, and if so, what have been the issues/results? Is my IRB going to freak out?
Will the students get annoyed? Or will it be a positive experience that gets them
started on the path to activism??

I look forward to any experiences, thoughts, or comments anyone could share.

Best wishes,

* * * * * * * * * * * * * *
Leah S. Horowitz, Ph.D.
Assistant Professor of Geography
Global Leadership and Sustainable Development Program
Hawai‘i Pacific University
1188 Fort Street Mall, Suite 313
Honolulu, Hawai‘i 96813-2713
....   ....   .....
I just completed teaching a one-term course on applied environmental activism (3rd
year undergrad). As far as I know, this may be a first of its kind in Canada. It was
lots of fun and the students enjoyed it tremendously and learned a lot doing in.
Here is a link to a story about it:

Group-based work is key for the activism project work (I recommend a minimum of 3,
maximum of about 7 or 8 per project group), but group work poses challenges for
evaluation, so I also included some individualized work alongside that (e.g., they
had to write short essay papers researching and evaluating such things as the Occupy
Movement and Keystone Pipeline protest). Ongoing communication between you and the
project groups and the wider class is central, both for learning and for management
of the course. At least half of every 3 hour meeting each week was spent de-briefing
and interrogating the class projects (of which there were 5) with the entire class
(n = 22 students), as these projects developed, encountered obstacles, made
progress, etc.

Give the students lots of room to be creative, but keep in mind the short time frame
they are working under so encourage projects that are modest and realistic in terms
of achieving something concrete. Keep a close watch on developments to ensure the
actions of the students in no way risk stepping outside the letter of the law or
other regulations pertaining to student activities on or off campus. Make sure your
senior university administrators know you are doing such a course and are supportive
in case any controversies arise out of the student activities. So far, we have had
nothing serious arise, but one can't always predict in advance such things.

Among our classes accomplishments this year were the completion of a protest march
(see photo in above story) and youtube video raising awareness about the Northern
Gateway pipeline (check it out:; a
community banquet to raise awareness about local food issues (attended by 150
people); two local Town Council-supported resolutions in support of, respectively,
the banning of plastic bags in stores and the serving of shark fin soup in local
restaurants; and several online and paper petitions supporting the aforementioned
activities and the proposal to build a local pedway over the highway to encourage
safe walking and bike use. Not bad for a 3-month class, but our university does have
a relatively highly engaged population of students, with a tradition of
environmental and social justice activism of various sorts. It is in part for this
reason that I decided to formalize such activities in a classroom setting like this.


"Bradley Walters"  

jueves, 10 de enero de 2013

And now our search for love is really our search for our other split-apart half.

Hedwig and the Angry Inch  and Plato’s Symposium

Toward the beginning of the movie, we get a charming re-telling of Plato’s myth of how there used to be three types of humans on earth, each with four legs and arms, two faces, etc. Some looked like a man and a woman all rolled up together, others like two men or two women. They were so happy that the gods became jealous and split them in two, moving the scar around to our bellies so we would always remember. And now our search for love is really our search for our other split-apart half.

......   ....   .....   ---   ----              --------------

es un sindrome sistémico: 




  1. Animal echolocation - Wikipedia, the free encyclopedia - Traducir esta página
    Echolocation, also called biosonar, is the biological sonar used by several kinds of animals. Echolocating animals emit calls out to the environment and listen to ...
  2. Human echolocation - Wikipedia, the free encyclopedia - Traducir esta página
    Human echolocation is an ability of humans to detect objects in their environment by sensing echoes from those objects. By actively creating sounds – for ...

    The Mirror Neurons System:

    -------  -------    ------------           ---                 ---------               ------


    [LIBRO] Abduction, reason, and science: Processes of discovery and explanation.

    L Magnani - 2001 -
    Abstract 1. Philosopher CS Peirce coined the term" abduction" to refer to inference that
    involves the generation and evaluation of explanatory hypotheses. Philosophers of science
    have recognized the importance of abduction in the discovery and evaluation of scientific ...

    J Nubiola - Razón y palabra, 2001 -
    Hace unas pocas semanas leía con vivo interés la necrológica de Jon Barwise en la última
    Newsletter de la American Philosophical Association. En unas líneas emotivas, Jon Dorbolo
    recordaba cómo Barwise insistía en que la lógica no es jugar con símbolos, sino que es la ...

    [HTML] ¿ Hay una" lógica" de la abducción

    M Hoffmann - 6 (9) Congreso de la IASS-AIS, 1997 -
    ... Para transformar la noción psicológica de "sorpresa" en una forma más lógica, podría decirse ...
    abductiva se va difuminando en el juicio perceptual sin una línea de demarcación clara entre
    ellos" (CP 5.181, 1903) podemos también decir que cada abducción ante "hechos ...

    [PDF] La abducción como cambio epistémico: CS Peirce y las teorías epistémicas en inteligencia artificial

    A Aliseda - Analogía, 1998 -
    ... filosófico peirceano. En este trabajo nuestro interés fundamental es concentrarnos
    en la forma lógica de la abducción propuesta por Peirce, en particular, en el aspecto
    que el elemento sorpresa juega en ella. Nuestro objetivo ...

    [DOC] La sorpresa como invitación a jugar con las creencias

    CA San Juan -
    ... La sorpresa es un prurito intelectual aunque el observador pueda decidir no rascarse. ... cuándo,
    cómo y por qué nos sorprendemos, a partir de la obra de Pierce los filósofos de la ciencia han
    estudiado la abducción buscando explicar y dar cuenta de una lógica de los ...

    [PDF] Abducción en el contexto del descubrimiento científico

    RJR Rodríguez - 2005 -
    ... La conexión entre la lógica abductiva y la tran- sición epistémica, entre los estados mentales
    de duda y creencia se ve muy claramente en el hecho de que la sorpresa sea la ... En general se
    considera el papel de la abducción como el mecanismo para generar las explicaciones ...

    [HTML] Peirce, la Abducción y la Investigación Científica

    R Espejo - Observaciones filosóficas, 2008 -
    ... antes de que yo clasificara la abducción como una inferencia, reconocían los lógicos que la ... de
    adoptar una hipótesis explicatoria - que es justamente lo que la abducción es - estaba ... Es por
    medio de sorpresa como la experiencia enseña todo lo que pretende enseñarnos 20 ". ...

    Peirce, abducción y práctica médica

    DE Niño - 2001 -
    ... Con o sin Sorpresa Explicación No creativo La sorpresa no se plantea No explicación Creativo ...
    No. El que se hayan venido haciendo correctamente los diagnósti- cos muestra que, dada la
    naturaleza lógica por la cual se realizan, es decir, por vía de la abducción, en la que ...

    [CITAS] Territorio Borges: y otros ensayos breves

    JB Rivera - 2000 - Atuel

    Hipótesis sobre la abducción en el enredo de las argumentaciones: análisis de una investigación en curso

    J Ferreira - La Trama de la Comunicación, 2010 -
    ... O signo de três. São Paulo: Perspectiva, 2004. NINO, Douglas. “Peirce, abdução y práctica
    médica”. Disponível em 2008 NUBIOLA, Jaime. “La
    abducción o lógica de la sorpresa”. Razon y Palabra. Número 21. 2009. ...

    [CITAS] Filosofía de la abducción

    E Anderson Imbert - 1992 -
    ... Presiente que está a punto de averiguar por qué le causaron sorpresa. Advierte,
    entre los componentes de esos fenómenos, una curiosa relación. ... Cómo atribuir
    a la abducción una forma lógica si su origen es instintivo? ...

    ---------------------             -----------           ----------


    ¿Cuanta gente fué a la fiesta y se salió de la fiesta porque había demasiado gente? (por sentir claustrofobia) 

    La ratonera masiva del Madrid arena pone al desnudo nuestra insuficiencia de alertas sensoriales para nuestra supervivencia.

    Cada enfermedad descrita por occidente, en especial las mentales, son sus propios sintomas como sociedad multi individual, la esquizofrenia del capitalismo. 


    ¿no es otra claustrofobia? 

    ¿y la del avión?,or.r_gc.r_pw.r_qf.&bvm=bv.1357700187,d.ZG4&fp=3be6e48becedd1fd&biw=994&bih=636

    o de como el cerebro se alimenta más hacia fuera, que hacia dentro; no es que tengan un gps en el cerebro, sino que su atencion directa e imprescindible al territorio, se refleka evidentemente en el cerebro, pues así lo trabajan más que quienes conducen con itinerarios pre-programados, y por consiguiente, tambien aquellos, mandos intermeidios, es decir, la parte media, que sostiene la piramide, cuyo trabajo tecnico es con papeles y superficies planas, pantallas, etc, sin un contacto continuado, dinámico y creativo, con el ecosistema,,,

miércoles, 9 de enero de 2013

Corpus callosum: musician and gender effects

Dennis J. Lee,1,2 Yi Chen1 and Gottfried Schlaug1

Previously we found that musicians have signi¢cantly larger anterior
corpus callosum(CC). In the current study,we intended to replicate
and extend our previous results using a new and larger
sample of gender-matched subjects (56 right-handed professional
musicians and 56 age- and handedness-matched controls). We
found a signi¢cant gender musicianship interaction for anterior
and posterior CC size; male musicians had a larger anterior CC
than non-musicians, while females did not show a signi¢cant e¡ect
of musicianship. The lack of a signi¢cant e¡ect in females may be
due to a tendency for a more symmetric brain organization and a
disproportionately high representation of absolute pitch (AP) musicians
among females. Although a direct causal e¡ect between
musicianship and alterations in the midsagittal CC size cannot be
established, it is likely that the early commencement and continuous
practice of bimanualmotor training serves as an external trigger
that can in£uence midsagittal CC size through changes in the
actual callosal ¢ber composition andin the degree ofmyelinization,
which will have implications for interhemispheric connectivity.
NeuroReport14:205^209 c 2003 LippincottWilliams &Wilkins.
Key words: Absolute pitch; Corpus callosum; Gender; Laterality; Magnetic resonance imaging; Motor skills; Music; Plasticity

Differential rearing affects corpus callosum size and cognitive function

Differential rearing affects corpus callosum size and cognitive function of rhesus monkeys

  • Department of Psychiatry and Behavioral Sciences, Yerkes Regional Primate Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA


This study investigated the effects of different rearing conditions on neural and cognitive development of male rhesus monkeys (Macaca mulatta). Infants raised individually in a nursery from 2 to 12 months of age (NURSERY, n=9) were compared to age-matched infants raised in a semi-naturalistic, social environment (CONTROL, n=11). Various brain regions were measured by MRI. Although overall brain volumes did not differ between NURSERY and CONTROL animals, corpus callosum (CC) size, measured in mid-sagittal sections, was significantly decreased in the NURSERY group. Group differences were most evident in the posterior aspects of the corpus callosum and appeared to result from changes in the number of cross-hemispheric projections rather than from a decrease in cortical gray matter volume. The decrease in corpus callosum size in the NURSERY animals persisted after 6 months of social housing in a peer-group. Rearing group differences were not found in other structures analyzed, including the hippocampus, cerebellum and anterior commissure. In cognitive testing, NURSERY animals had more difficulty acquiring the delayed non-matching to sample (DNMS) task, but showed no deficits in subsequent memory performance when a 2 or 10 min delay was imposed. The NURSERY infant monkeys were also impaired in object, but not in spatial, reversal learning, although there were no differences in a simple object discrimination task. The cognitive deficits exhibited by the NURSERY animals were significantly correlated with the alterations found in the CC. In summary, rearing environment was associated with sustained differences in cross-hemispheric projections, white matter volume and cognitive performance.


  • Rearing environment;
  • Corpus callosum;
  • Cerebral cortex;
  • MRI;
  • Cognition;
  • Rhesus monkey

1. Introduction

Social experience appears to be essential for normal primate behavioral development. In rhesus monkeys, social deprivation early in development is associated with profound and enduring increases in abnormal self-directed (autistic-like) behaviors, alterations in normal social behavior, deficits in exploration, communication, emotionality and sexual and maternal behaviors 33 and 63. The precise behavioral consequences depend on the extent, the duration, and the age at which social deprivation occurs, but there is little question that infants are more vulnerable than adults and that isolation through the first year leads to irreversible changes in behavior [33].
Although there has been extensive research into the mechanisms by which social deprivation alters behavioral development, there have been relatively few studies of its neurobiological consequences. Indeed, we know very little about how social experience contributes to normal neural development and, as a consequence, normal cognitive function in primates. Early studies in macaques reported decreases in dendritic branching in cortical stellate cells [62]and cerebellar Purkinje cells [22], but these changes likely result from rearing in conditions of low environmental complexity rather than a specific loss of social interaction. Other groups have described neurochemical changes subsequent to early social deprivation, such as decreases in dopamine innervation of the neocortex and striatum, but not in other structures, such as the amygdala [47]. These results, however, are confounded by aging effects which might have contributed to group differences. More recent studies that have compared juvenile monkeys (19–27 months) raised in isolation or social housing have found no differences in dopaminergic or noradrenergic innervation of the hypothalamus, or in corticotropin releasing hormone content in the hypothalamic paraventricular nucleus 26 and 27.
To our knowledge, there has been no previous investigation of how social experience contributes to primate brain development using structural brain imaging. Several studies in rodents have described changes in neuronal morphology based on environmental enrichment 1, 15, 18, 31, 41 and 64and clinical studies using MRI have described decreased hippocampal volume in adult post-traumatic stress disorder patients with a history of childhood abuse 10 and 61. The current study used high resolution MRI to investigate differences in neural development associated with differential rearing of rhesus monkeys (Macaca mulatta). In addition, subsets of these animals were assessed for specific cognitive functions, such as visual recognition memory, visual formation habit, and executive function by means of the delayed non-matching to sample (DNMS), simple object discrimination and object/spatial reversal learning tasks, respectively.

2. Material and methods

2.1. Animals

The experimental animals were obtained from a population of macaque infants originally reared for immunologic studies. These studies required nursery-rearing of the infants from the 7th until the 48th week of age (NURSERY, n=9). Nursery-reared monkeys were housed in individual cages in rooms with automatically regulated temperature and lighting conditions (light/dark, 0600 h/1800 h). These animals could, at any time, see and hear other animals in the colony, and had physical contact with caretakers but not with conspecifics. Each monkey had access to a fleece board for contact comfort and toys for manipulation. At the end of the 48th week, a subset of these animals was introduced into a peer-group with animals of the same condition (NURSERY-PEER, n=5), while the rest continued to be individually housed (NURSERY-IND, n=4). The control group (CONTROL, n=12) consisted of age-matched infants raised in a semi-naturalistic, social environment under field conditions. A subset of CONTROL animals were caged as a peer-group adjacent to the NURSERY peer-group (n=4) beginning at 48 weeks of age. NURSERY animals received milk formula until 4 months old; after that age, all animals were fed a diet of Primate Purina Chow supplemented with fruit and vegetables; water was available ad libitum. Cognitive testing was started at approximately age 12 months on both NURSERY and CONTROL peer-housed groups; the MRI study was performed at age 18 months. All data in this report were derived from males. All procedures were approved by the Emory University IACUC (MRI/cognitive protocol #:059-96Y and rearing protocol #:081-95Y).

2.2. Procedures

2.2.1. Quantitative brain magnetic resonance imaging MRI procedure
A total of 11 CONTROL and 9 NURSERY rhesus macaques were studied. MRI scans were obtained with a high-field strength (1.5 T) MR imaging unit (Philips Medical Systems, the Netherlands) on animals deeply anesthetized with sodium pentobarbital (15–30 mg/kg BW, i.v.) using an extremity coil. T1-weighted images were acquired using a gradient echo protocol with the following parameters: TR=19 msec, TE=8.5 ms, field of view=180 mm, flip angle=35°, matrix=256×256, number of signals averaged=8, slice thickness=1.2 mm, interslice overlap=0.6 mm. T2-weighted images were also acquired using an inversion recovery protocol with the following parameters: TR=3000 ms, TE=40 ms, TI=200 ms, field of view=260 mm, flip angle=180°, matrix=256×512, number of signals averaged=2, slice thickness=2.0 mm (non-overlapping). The inversion recovery protocol optimizes gray-white contrast and allows some structures to be delineated more clearly than with the gradient echo scan. Image analysis
Images were transferred to a SUN computer workstation and analyzed by means of an image-analysis software program (Easyvision, Philips Medical Systems, The Netherlands). All scans were reformatted into sagittal, coronal and axial orthogonal planes (the latter, defined by a line connecting the anterior and posterior commissures). The T1-weighted scans were used to measure whole brain and cerebellar volumes. In each slice, the structure of interest was selected through a combination of computerized thresholding based on pixel signal intensities and manual editing. Easyvision estimates structure volume by summing its volume across all slices in which it is present.
The corpus callosum (CC) and anterior commissure (AC) were manually traced from 3 midsagittal sections (0.5 mm thick), where the spinal cord, cerebellum, fourth ventricle and colliculi could be seen in their maximum extension. After the entire CC was traced, it was divided into 5 subdivisions, according to a modification of the method described by Biegon et al. [9]. Briefly, the cursor was positioned at the most anterior point of the genu of the CC, and a ruler tool was swivelled toward the most posterior point of the splenium of the CC. The position at which the intersection of the posterior end of the splenium produced the longest distance was used to provide the longest axis of the CC, which was measured and divided into five parts: the anterior 20% (first fifth) defined as genu, the middle 60% as midbody (MB, with three subdivisions: rostral (rMB), medial (mMB) and caudal (cMB)), and the posterior 20% (last fifth) defined as splenium [19]. The area of each of the 5 subregions of the CC was measured and the total area calculated as the sum of its five segments (Fig. 1).
Full-size image (30 K)
Fig. 1. (A) Midsagittal MR T2-weighted image through the corpus callosum of a CONTROL rhesus monkey infant. (B) Schematic diagram of the five corpus callosum subregions studied; from rostral to caudal: genu, rostral midbody (rMB), medial midbody (mMB), caudal midbody (cMB) and splenium.
Prefrontal brain volume was estimated based on criteria used in human MRI studies 12, 24 and 25where a coronal plane perpendicular to the AC-posterior commissure line was used to determine the volume of brain in front of the most anterior point of the genu of the CC. This region overlaps primarily with prefrontal cortex in rhesus monkeys, excluding 50% of area 25 5 and 30. Three coronal sections (0.5 mm thick) caudal to the CC splenium were analyzed within the parietal lobe according to primate neuroanatomical Refs. [35]. Gray and white matter areas were manually traced through the right and left prefrontal and parietal cortices and their volumes measured. In addition, the ratio of gray/white matter was calculated. The boundaries of the prefrontal and parietal cortices were determined from internal landmarks. In a separate study, we have shown, with a postmortem validation, that gray/white matter segmentation obtained from MRI correlates over 0.97 with values obtained from measures on fresh brain material [J.K. Rilling and T.R. Insel, unpublished observations].
The left and right hippocampi were manually traced through their whole rostrocaudal extension from coronal T2 images, and the successive areas were integrated to arrive at a volume estimate. The inversion recovery protocol provided a strong contrast between gray and white matter, so that the hippocampal formation (including: (a) the Cornu Ammonis -CA1 to CA4- or hippocampus proper (b) the dentate gyrus and (c) the subiculum) could be traced following the neuroanatomical landmarks defined for the primate [56].
When the size of the neural structure analyzed was significantly correlated with total brain volume, the ratio of structure volume to total brain volume was used as the independent variable for statistical analysis; otherwise, the absolute structure volume was used (Table 1).
Table 1. Correlations of brain volume with body weight and size of different neural structures measured by MRI

Brain volumeCorrected for total brain vol?
Body weightr=0.38, n.s.
Corpus callosumr=0.68, p<0 .005=".005" td="td">yes
Anterior commissurer=0.27,
Prefrontal cortexr=0.6, p<0 .01=".01" td="td">yes
Parietal cortexr=0.84, p<0 .0001=".0001" td="td">yes Measurements reliability
Intra and inter-rater reliability of volume and area estimates were assessed using intraclass correlation coefficients (ICCs). Inter-rater reliability was verified by analysis of scans performed by a different experimenter (ICC were: r=0.95 for brain vol.; r=0.84 for cerebellum vol.; r=0.95 for CC area; r=0.97 for gray and r=0.92 for white cortical matter areas; r=0.87 for hippocampal vol.); intra-rater reliability was assessed by measuring a subsample of the brains a second time, at least two months later (ICCs: r=0.99 for brain vol.; r=0.98 for cerebellum vol.; r=0.97 for CC area; r=0.91 for gray and r=0.86 for white cortical matter areas; r=0.93 for hippocampal vol.).

2.2.2. Cognitive study

At 12 months of age NURSERY (n=5) and CONTROL (n=3) monkeys were randomly selected for cognitive studies. Animals were given a standard battery of cognitive tests, which were administered in a Wisconsin General Testing Apparatus (WGTA) inside a darkened, sound-shielded room, with additional sound-masking provided by a white-noise generator. During intertrial and retention intervals, an opaque screen separated the macaque infant from the three-well tray, and a one-way vision screen separated the animal from the experimenter. The cognitive tests performed included the acquisition and performance phases of the delayed non-matching to sample (DNMS), simple object discrimination, as well as spatial and object-reversal learning. Delayed non-matching to sample
The DNMS is a recognition memory task that assesses the monkey's ability to distinguish a novel from a familiar stimulus following a specific delay interval [49]. Before testing began, all subjects were trained to displace a plaque covering the food reward; this pre-training phase was completed when the animal displaced the plaque in 20 consecutive trials in a 20 trial session. In the acquisition phase of the DNMS, a sample object is presented over the central, baited food well of the three-well tray. Once the monkey displaces the sample object to retrieve the food reward, a screen is lowered between the animal and the testing tray. A 10-s second delay is imposed during which time one of the lateral wells is baited, as pre-determined by a pseudo-random sequence, and covered with a novel object while the sample object is positioned over the other lateral well. On this recognition trial, successful performance is defined as displacement of the novel object to obtain the reward. After an inter-trial interval of 20 seconds, a different pair of objects is used. Twenty trials per day are given until the animal reaches a learning criterion of 90 correct responses in 100 consecutive trials in a given 5-day period. The outcome measures for the acquisition phase of the DNMS were the number of trials and incorrect responses (errors) made by the monkey in reaching criterion.
Once the DNMS learning criterion was attained, a 2- or a 10-min delay was introduced between the sample presentation and recognition trial. Ten trials per day were given for 10 days for each delay. The delay imposed is a challenge for the monkey's recognition memory and the outcome measure consisted of correct answers made during those 100 trials. Simple object discrimination
This task tests the monkey's ability to discriminate between two objects, one that is always baited and one that is never baited. Thirty trials, with 20 s between trials, were given each day and a pseudo-random sequence determined which of the lateral wells was baited during each trial. A correct response involves the monkey displacing the baited object. Completion of the task consisted of 27 correct responses in 30 consecutive trials within a single session. The outcome measures were the number of errors made to reach criterion. Spatial and object reversal learning
In the spatial reversal task, two identical gray plaques were placed over the left and right wells of the tray. Initially, either the left or the right side was designated as correct, and that side was always baited. The monkey obtained the reward by displacing the plaque always on the appropriate side. When the monkey attained a criterion of 90% correct responses in 30 consecutive trials, a series of three reversals began, with the correct side changing in each reversal. After the spatial reversal task was completed, an object reversal task was started. Two different objects were used to cover the lateral wells, with one of the objects randomly chosen to be correct. After the monkey reached criterion (90% correct responses in 30 trials), the opposite object was baited through a series of three reversals. Both procedures have been described in detail elsewhere [43]. The outcome measures for both spatial and object reversals were the number of trials and the number of errors to reach criterion after each reversal.

2.2.3. Statistical analysis

The central question in this experiment was whether groups of animals reared under different conditions (CONTROL vs. NURSERY) would differ in brain anatomy or cognitive measures. For simple group comparisons on independent means, we used the two-tailed Student's t-test (or the non-parametric Mann–Whitney U-test when there was non-homogeneity of variance). For analyses with multiple related outcome measures (e.g., corrected areas of the different CC subregions or reversals in the object and spatial reversal learning tasks), we used a repeated measures ANOVA to evaluate differences between NURSERY and CONTROL groups. We then used the Hotelling T2 multiple comparison test to explore the source of significant effects. When differences were found between the CONTROL and NURSERY groups, a subsequent analysis was conducted in order to verify if NURSERY-IND animals were different from NURSERY-PEER. The aim of this latter comparison was to detect if the introduction of NURSERY animals into a peer group for 6 months improved the alterations caused by such a rearing condition. In the case of the CC, we also performed a repeated measures analysis of covariance to evaluate inter-group differences between `absolute' areas of the different subregions, after adjustment for brain volume. This alternative analytical procedure was used to validate the results obtained from the repeated measures ANOVA, where the `corrected' areas were compared.
Relationships between the brain volume and the size of the different neural structures studied by MRI, between the CC size and cognitive measures, as well as among sizes of the different CC subregions, were assessed with Pearson product–moment correlations. The relationships among the different CC subregions were analyzed by first using regression models to fit each region to brain volume, and then correlating the residuals of each model. In this way, we made sure that the effect of the brain volume was eliminated from each region comparison. For all analyses, a confidence level of p<0 .05=".05" analysis="analysis" by="by" cary="cary" considered="considered" data="data" institute="institute" means="means" nc="nc" of="of" p="p" performed="performed" sas="sas" significant.="significant." software="software" statistical="statistical" usa="usa" was="was">

3. Results

3.1. General observations

As expected from previous descriptions 33 and 63, NURSERY animals exhibited a syndrome of abnormal behaviors, including increased locomotor activity, as well as stereotypic, self-injurious, self-oral, or clinging behaviors not shown by the CONTROL infants. They also showed reduced social contact in comparison to CONTROL animals [57]. One of the animals in the CONTROL group had to be released from the study due to chronic illness following his transfer from the Field Station social group to the caged peer-group, leaving 11 CONTROL infants for MRI and 3 for cognitive studies.

3.2. Quantitative MRI

As shown in Table 2, CONTROL and NURSERY animals were not different in body weight (t18=-0.21, Student's t-test), overall brain volume (U=125, Mann–Whitney U-test), cerebellar volume (t18=0.09, t-test), or hippocampal volume (t18=-1.86, t-test). The corpus callosum (CC) was traced in mid-sagittal sections and subdivided into 5 different regions (genu, rostral midbody -rMB-, medial midbody -mMB-, caudal midbody -cMB- and splenium) as represented in Fig. 1. Although the CC length was not different between groups (t18=−0.5, t-test; Table 2), its mean area (corrected for brain volume) was significantly smaller in NURSERY than in CONTROL animals (t18=4.73, p<0 .001=".001" em="em">t
-test), as shown in Fig. 2A. When the five different subregions of the CC were considered in the analysis (Fig. 2B), the effect of both rearing condition and subregion were significant (F2,17=13.63, p<0 .001=".001" and="and" em="em">F4,68=400.73, p<0 .0005=".0005" anova="anova" as="as" em="em" interaction="interaction" measures="measures" rearing="rearing" repeated="repeated" respectively="respectively" subregion="subregion" the="the" was="was">F8,68=2.91, p<0 .01=".01" a="a" adjusting="adjusting" among="among" analysis="analysis" and="and" animals="animals" between="between" both="both" brain="brain" but="but" cc="cc" cmb="cmb" comparison="comparison" comparisons="comparisons" control="control" controls="controls" covariance="covariance" differed="differed" differences="differences" each="each" effect="effect" em="em" especially="especially" for="for" groups="groups" had="had" identical="identical" in="in" indeed="indeed" indicate="indicate" infants="infants" its="its" measures="measures" mmb="mmb" nurs-peer="nurs-peer" nursery-rearing="nursery-rearing" nursery="nursery" obtained="obtained" of="of" on="on" pairwise="pairwise" performed="performed" repeated="repeated" results="results" robust="robust" showed="showed" significantly="significantly" size="size" sizes="sizes" smaller="smaller" subregion="subregion" subregions.="subregions." subregions="subregions" that="that" the="the" these="these" to="to" volume.="volume." was="was" were="were" when="when">p<0 .05=".05" em="em" hotelling="hotelling">T2 post-hoc test). The Hotelling T2 test did not detect significant differences between the NURS-PEER and NURS-IND subgroups for any of the CC subregions analyzed, indicating that the reduced CC size persisted in the NURSERY-reared animals even after 6 months of peer-group housing.
Table 2. Age, body weight and measurements obtained in different neural structures by magnetic resonance imaging in CONTROL and NURSERY infant macaques

CONTROL (n=11)NURSERY (n=9)p values
AGE (months)18.32±0.2517.55±0.26t18=2.09, n.s.
BODY WEIGHT (kg)2.99±0.093.01±0.11t18=−0.21, n.s.
BRAIN vol (cc)78.10±1.9882.99±2.38U=125, n.s.
CEREBELLAR vol (cc)7.33±0.197.31±0.21t18=0.09, n.s.
CC length (mm)29.98±0.4830.38±0.68t18=−0.5, n.s.
AC area (mm2)3.97±0.174.23±0.11t18=−1.24, n.s.
HIPPOCAMPUS vol (cc)0.84±0.030.90±0.03**t16=−1.86, n.s.
Corrected PREFRONTAL vol ×1028.3±0.167.8±0.23t18=1.81, n.s.
Corrected PARIETAL vol ×1022.48±0.042.53±0.04*t17=−0.80, n.s.
Results are presented as mean±S.E.M.Student's t-test was used to examine the statistical significance of between-group differences in the measurements obtained, except for brain vol, where a Mann-Whitney U-test was conducted.*n=8; **n=7; n.s.: non-significant.
Full-size image (12 K)
Fig. 2. (A) Total corpus callosum (CC) corrected area of CONTROL and NURSERY animals (*p<0 .001=".001" em="em">t
18=4.73; Student's t-test). (B) Corrected area of the different CC subregions. Both groups of NURSERY infants (NURS-IND and NURS-PEER) showed significantly smaller CC subregions in comparison to CONTROLS (repeated measures ANOVA: F2,17=13.63, p<0 .001=".001" by="by" em="em" group="group">F4,68=400.73, p<0 .0005=".0005" by="by" em="em" subregion="subregion">F8,68=2.91, p<0 .01=".01" and="and" by="by" cmb="cmb" effect="effect" em="em" especially="especially" group="group" in="in" interaction="interaction" mmb="mmb" robust="robust" subregion="subregion" the="the" this="this" was="was">p<0 .05=".05" em="em" hotelling="hotelling">T2 post-hoc test; CONTROL vs. NURSERY). The Hotelling T2 test did not detect significant differences between NURS-PEER and NURS-IND animals for any of the CC subregions analyzed. Data were ln transformed for statistical analysis. rMB: rostral midbody; mMB: medial midbody; cMB: caudal midbody.
To determine if differences in the CC size were orderly, we examined the correlations between the areas of the different CC subregions, after eliminating the effect of brain volume (Table 3). In CONTROL macaque infants, positive correlations were detected between the sizes of the genu and rMB (Pearson's r=0.76, p<0 .01=".01" and="and" cmb="cmb" em="em" genu="genu">r
=0.66, p<0 .05=".05" and="and" em="em" mmb="mmb" rmb="rmb">r=0.84, p<0 .01=".01" and="and" cmb="cmb" em="em" rmb="rmb">r=0.86, p<0 .001=".001" and="and" as="as" between="between" cmb="cmb" em="em" mmb="mmb" well="well">r=0.86, p<0 .001=".001" animals="animals" associations="associations" between="between" cc="cc" correlations="correlations" disrupted="disrupted" em="em" found="found" genu-rmb:="genu-rmb:" in="in" most="most" no="no" nursery="nursery" of="of" significant="significant" since="since" strong="strong" subregions="subregions" these="these" those="those" were="were">r=0.22; genu-cMB: r=0.19; rMB-cMB: r=0.24; mMB-cMB: r=0.18), except between rMB and mMB (r=0.96, p<0 .0005=".0005" p="p">
Table 3. Correlations between the size of different corpus callosum subregions after eliminating the effect of brain volume in both CONTROL and NURSERY groups

Genu-rMBr=0.76, p<0 .01=".01" td="td">r=0.22, n.s.
Genu-cMBr=0.66, p<0 .05=".05" td="td">r=0.19, n.s.
rMB-mMBr=0.84, p<0 .01=".01" td="td">r=0.96, p<0 .0005=".0005" td="td">
rMB-cMBr=0.86, p<0 .001=".001" td="td">r=0.24, n.s.
mMB-cMBr=0.86, p<0 .001=".001" td="td">r=0.18, n.s.
Relationships were assessed with Pearson product-moment correlations.In order to eliminate the effect of brain volume from each region comparison, we first used regression models to fit each region to brain volume, and then the residuals of each model were correlated.n.s.: non-significant; rMB: rostral midbody; mMB: medial midbody; cMB: caudal midbody.
The anterior commissure (AC), another structure containing interhemispheric fibers, was not different between the two rearing conditions (t18=−1.24, t-test; Table 2).
The prefrontal and parietal total volumes (corrected for brain volume) were not significantly different between NURSERY and CONTROL infants (Table 2). Following segmentation, we found no differences in gray matter volume, but white matter appeared lower in the NURSERY group (Fig. 3). The differences were statistically significant for parietal cortex (t17=2.33, p<0 .05=".05" em="em">t
-test) and marginally significant for prefrontal cortex (t18=2.07, p=0.053; t-test). The parietal gray/white matter ratio was significantly increased in NURSERY animals, when compared to CONTROLs (t17=2.58, p<0 .05=".05" em="em">t-test).
Full-size image (13 K)
Fig. 3. Gray and white matter corrected volumes from parietal and prefrontal lobes. NURSERY infants showed a significant decrease in parietal white matter and, consequently, an increase in the gray/white matter ratio (*p<0 .05=".05" em="em">t
17=2.33 and t17=2.58, respectively; Student's t-test) in comparison to CONTROL animals. The prefrontal white matter was also reduced in the NURSERY group, but the effect was not so strong (#p=0.053, t18=2.07; t-test).

3.3. Cognitive deficits

NURSERY monkeys at 1 year of age exhibited several cognitive deficits. NURSERY monkeys required more trials (t6=3.0, p<0 .05=".05" em="em">t
-test) and made significantly more errors (t6=4.15, p<0 .01=".01" em="em">t-test) than CONTROLs in reaching criterion on the DNMS (Fig. 4A). Once the criterion was achieved, however, NURSERY animals performed as well as CONTROLs during the 2- and 10-min delay condition of the DNMS (2-min: t6=−0.96 and 10-min: t6=-0.1; t-test) as shown in Fig. 4B. Acquisition of the DNMS in the NURSERY group was associated with the size of the caudal subregions of the CC, as demonstrated by the negative correlations between the trials and errors to reach criterion and the cMB and splenium corrected areas (trials: rsplenium=−0.83, p=0.08; errors: rcMB=−0.88, p=0.05 and rsplenium=−0.81, p=0.09). The performance of the 2- and 10-min delay phase of the DNMS, however, was strongly associated with the size of the genu of the CC, as shown by the significant positive correlation between the number of correct answers and the genu's corrected area (2-min: r=0.93, p<0 .05=".05" 10-min:="10-min:" em="em">r=0.82, p=0.09).
Full-size image (15 K)
Fig. 4. (A) Delayed non-matching to sample (DNMS) acquisition was impaired in NURSERY infant macaques, which required more trials (*p<0 .05=".05" em="em">t
6=3.0; Student's t-test) and made more errors (**p<0 .01=".01" em="em">t6=4.15; t-test) than the CONTROL group. The bottom part of the graph represents a diagram of the corpus callosum showing the correlations between the size of its subregions and the trials and errors to reach criterion in the NURSERY group; during the acquisition of the DNMS, negative correlations were detected between the trials and errors to reach criterion and the cMB and splenium corrected areas (trials: rsplenium=−0.83, p=0.08; errors: rcMB=−0.88, p=0.05 and rsplenium=−0.81, p=0.09). (B) Once animals reached criterion, a delay of 2 or 10 min was imposed to challenge recognition memory ability. The performance of this delay phase of the DNMS was not different in both groups of animals (2-min: t6=−0.96, n.s.; 10-min: t6=−0.1, n.s.). Bottom part of the graph: in the NURSERY animals the performance of the delay phase of the DNMS was strongly associated with the size of the genu of the CC, as shown by the significant positive correlation between the number of correct answers and the genu's corrected area (2-min: r=0.93, p<0 .05=".05" 10-min:="10-min:" em="em">r=0.82, p=0.09).
In order to verify if the alterations found in the DNMS were due to impaired learning or to deficits such as attention or motivation, the animals were subjected to a simple object discrimination task. NURSERY and CONTROL groups did not differ in the acquisition of this task, as reflected in the number of errors to reach criterion (t6=1.75, t-test; Fig. 5). Interestingly, a significant negative correlation was detected between the number of errors to reach criterion and the cMB corrected area (r=−0.97, p<0 .01=".01" group.="group." in="in" nursery="nursery" p="p" the="the">
Full-size image (4 K)
Fig. 5. Simple object discrimination task. No statistically significant differences were found between NURSERY and CONTROL groups in the acquisition of this task, as reflected in the number of errors to reach criterion (t6=1.75, n.s.; Student's t-test). Bottom: a significant negative correlation was detected between the number of errors to reach criterion and the cMB corrected area (r=−0.97, p<0 .01=".01" group.="group." in="in" nursery="nursery" span="span" the="the">
CONTROL and NURSERY animals did not differ in the acquisition of either spatial or object reversal learning. However, the NURSERY group had more difficulties than the CONTROL, once the reversals were imposed (Fig. 6). For object reversal learning, the NURSERY group required more trials and made more errors during the three reversals than the CONTROL group (trials: F1,4=37.34, p<0 .005=".005" em="em" errors:="errors:">F
1,4=90.38, p<0 .001=".001" across="across" change="change" criterion="criterion" em="em" errors="errors" in="in" made="made" no="no" number="number" of="of" or="or" reach="reach" required="required" reversals="reversals" the="the" there="there" three="three" to="to" trials:="trials:" trials="trials" was="was">F2,8=0.58, n.s.; errors: F2,8=2.68, n.s.), nor was there a significant interaction of treatment group with reversal number (trials: F2,8=1.08, n.s.; errors: F2,8=0.99, n.s.). The NURSERY animals' shifting ability in the object reversal learning was strongly associated with the size of the CC midbody, as demonstrated by the significant negative correlations with the number of trials (rMB: r=−0.91, p<0 .05=".05" em="em" mmb:="mmb:">r=−0.89, p<0 .05=".05" and="and" em="em" errors="errors" rmb:="rmb:">r=−0.94, p<0 .05=".05" em="em" mmb:="mmb:">r=−0.93, p<0 .05=".05" and="and" between="between" control="control" criterion.="criterion." detected="detected" differences="differences" em="em" for="for" groups="groups" however="however" in="in" learning="learning" no="no" number="number" nursery="nursery" of="of" reach="reach" reversal="reversal" spatial="spatial" the="the" to="to" trials="trials" were="were">F1,5=1.01, n.s.) or errors (F1,5=1.85, n.s.). In this case, there was a change across the three reversals in the number of trials required, or errors made to reach criterion (F2,10=8.12, p<0 .01=".01" and="and" em="em">F2,10=8.26, p<0 .01=".01" but="but" detected="detected" em="em" group="group" interaction="interaction" no="no" number="number" of="of" respectively="respectively" reversal="reversal" significant="significant" treatment="treatment" trials:="trials:" was="was" with="with">F2,10=0.40, n.s.; errors: F2,10=0.79, n.s.). No significant correlations were found between spatial reversal learning performance and the size of the CC, either in the CONTROL or in the NURSERY group.
Full-size image (19 K)
Fig. 6. Object and spatial reversal learning. (A) NURSERY animals were impaired in object reversal learning, since they required significantly more trials (repeated measures ANOVA: F1,4=37.34, p<0 .005=".005" by="by" em="em" group="group">F
2,8=0.58, n.s. by number of reversals; F2,8=1.08, n.s. by group×number of reversals interaction) and made more errors (F1,4=90.38, p<0 .001=".001" by="by" em="em" group="group">F2,8=2.68, n.s. by number of reversals; F2,8=0.99, n.s. by group×number of reversals interaction) to reach criterion during the three reversals than CONTROLs. Bottom: diagram showing the correlations between the CC subregions' sizes and the trials and errors to reach criterion during the first reversal. (B) No significant differences were detected between CONTROL and NURSERY groups in spatial reversal learning (Trials: F1,5=1.01, n.s. by group; F2,10=8.12, p<0 .01=".01" by="by" em="em" number="number" of="of" reversals="reversals">F2,10=0.40, n.s. by group×number of reversals interaction. Errors: F1,5=1.85, n.s. by group; F2,10=8.26, p<0 .01=".01" by="by" em="em" number="number" of="of" reversals="reversals">F2,10=0.79, n.s. by group×number of reversals interaction). Bottom: No significant correlations were found between spatial reversal learning performance and the size of the CC subregions, either in the CONTROL or in the NURSERY group.

4. Discussion

NURSERY animals showed a decrease in CC midsagittal area (especially in its caudal aspects) accompanied by a decrease in white (but not gray) matter volume in parietal and prefrontal cortex. Nursery-rearing had no detectable effects on brain, cerebellar, hippocampal or prefrontal cortex volumes, or on the size of the AC. The alterations found in CC size persisted despite introduction of the NURSERY animals into a peer-group for 6 months. In relation to cognitive function, the NURSERY macaques were impaired on the acquisition, but not on the performance of a DNMS. The NURSERY animals also showed impairment in object, but not in spatial, reversal learning, although they learned a simple object discrimination task as readily as the CONTROL group. These cognitive deficits were significantly correlated with the alterations found in the CC. Taken together, these results suggest that nursery-rearing was associated with decreased cross-hemispheric projections, loss of parietal and prefrontal white matter and impaired acquisition of complex cognitive tasks.
Nursery-rearing is a complex experimental condition and the observed differences between the NURSERY and CONTROL groups could therefore be a consequence of several different aspects of the early environment. The behavioral abnormalities that accompany isolation rearing have been variously attributed to lack of mother and social contact 33 and 63, reduced somatosensory stimulation 33 and 55, or loss of controllability over the environment [48], any of which could contribute to the group differences observed in the present study.
In spite of these limitations, we can conclude that the midsagittal CC area was reduced in the NURSERY group when compared to the CONTROL. These differences were found after adjustment for brain volume and were especially robust in mMB and cMB. There was no evident measurement bias in identifying the mMB and cMB as CC axis length was not different in the two groups. The alterations found were not improved by introduction of the NURSERY animals into a peer-group for 6 months, consistent with the possibility that the changes are irreversible.
The CC of the rhesus monkey shows a topographic segregation of callosal fibers from different cortical regions along its anterior–posterior axis 50 and 52. The rostral half carries fibers from the prefrontal, premotor and motor areas, as well as anterior insular and anterior cingulate fibers, while the caudal half carries fibers originating in the parietal, temporal and occipital lobes. The reduced size detected in caudal CC subregions of NURSERY animals (especially robust in the mMB and cMB), may therefore reflect specific alterations in cross-hemispheric fibers originating in the primary and second somatosensory areas, posterior parietal association cortex, caudal superior temporal, posterior insular and posterior cingulate gyri, and primary auditory area 2, 11, 45, 50 and 60.
Unlike the CC, which contains interhemispheric fibers from all lobes, the AC contains fibers mainly from the caudal orbitofrontal and rostral temporal cortices 16 and 37. The absence of group differences in AC size suggests a region-specific effect of the rearing conditions on the cross-hemispheric projections. This is further supported by the fact that the strong associations between some CC subregions evident in CONTROL animals were disrupted in NURSERY animals, since no significant correlations were found between them.
A reduction in cross-hemispheric projections could result from a reduced number of callosal neurons, or from a reduction in the number of callosal axons (and/or in their myelination and growth) from the same number of neurons. The decrease in white (but not gray) matter volume found in the parietal and prefrontal cortices of NURSERY infants is consistent with the second possibility. In the primate brain, the frontal, parietal, and temporal association areas have dense and widespread callosal projections and terminations 40 and 51and the maturation of those tracts proceeds slowly [23], making them more vulnerable to the differential rearing conditions than other systems. Although the white matter loss may reflect a reduction in the number, myelination, and/or size or packing density of the callosal axons from the parietal and prefrontal cortices, it could equally reflect alterations in intracortical connectivity, since neocortical white matter consists of about ten-fold as many intra- as inter-hemispheric fibers [58].
Our observations are consistent with results from clinical studies in which the size of the middle and posterior subregions of the CC were reduced in autistic individuals 21 and 54and white matter volume loss was detected in the parietal lobes 13 and 14. These findings are particularly intriguing given the autistic-like behaviors (gaze avoidance, self-directed behaviors, stereotypies) of our NURSERY-reared monkeys, behaviors previously reported in monkeys reared in social isolation [33].
The reduced CC size found in the NURSERY animals is also consistent with Denenberg's [17]hypothesis that the callosal cross-sectional area would be larger in animals stimulated throughout development. Indeed, there are reports showing that early handling in rats (from PND1-21) provokes an increase in the adult CC size [8]and that rats reared in a complex environment show increased area in middle and posterior callosal thirds [38]. Now, how might early experience alter the size of the corpus callosum? First, it is unlikely that it affected the initial callosal projections, since the adult patterns of mosaic composition of axons in the CC and of callosal connections 42, 45, 51 and 59are present before birth in the rhesus monkey [44]. The postnatal development of the CC depends on, at least, two complex processes: axonal pruning and myelination 23, 36 and 44. As for pruning, it has been demonstrated that early sensorial experience affects which callosal neurons (or axons) are stabilized and which are eliminated during development [36]. In the rhesus monkey, callosal axon elimination after birth occurs in a rapid phase during the first 3 postnatal weeks, and in a second slow phase from 2–6 months of age, when 70% of axons are eliminated [44]. This occurs within groups of axons that are already in their correct location within the CC, due to retraction or cell death. A higher rate of elimination of callosal axons in the NURSERY animals during such a critical period of development (3–6 months) could have produced a reduction in the CC size, due to different factors in their early environment, such as the limited exposure to social and sensorial stimuli. The AC shows a different temporal pattern of pruning and myelination with relatively little loss of callosal axons after the third postnatal month [46]. The normal size of the AC in the NURSERY group in the face of reduced CC size may therefore reflect the later pruning and myelination of callosal fibers or nursery-rearing effect on specific callosal projections that are not present in the AC.
As for the second process, at 3–6 months all cortical areas in the rhesus monkey contain some myelin, but the myelination and axonal growth in tracts and layers involved in intra- or inter-cortical processing in association areas proceed slowly and are not complete until 2.5–3 years of age 23 and 44. Since our infant macaques had different rearing environments from 2–12 months of age, one might speculate that myelination of specific callosal (but also of intra-hemispheric) projections could have also been altered by some aspect of the NURSERY condition. The parallel reduction in parietal and prefrontal white matter volume detected in the NURSERY animals would support this interpretation. An altered impulse transmission secondary to a reduction in myelinated fibers could have affected the survival and functional maturation of cortical synapses [39]and, in consequence, higher cortical function.
The NURSERY macaques were impaired in acquisition of the DNMS, but performed normally in this task following delays as long as 10 minutes. This finding suggests an impairment in new learning, but not in performance of a visual recognition memory task. The results are analogous to alterations in acquisition, but not in the delay phase of DNMS reported in autistic children [E. Courchesne, personal communication] and in other situations such as aging [34]. The fact that NURSERY animals learned a simple object discrimination task as readily as controls suggests that differences in acquisition of DNMS were not attributable to an inadequacy of perception, attention, motivation, or stimulus-response association, since these same factors are required for visual discrimination learning tasks.
NURSERY monkeys were impaired in object, but not in spatial, reversal learning suggesting a task-specific impairment in learning plasticity (increased perseveration) which seems to be related to the type of information being processed (visual vs. spatial), rather than to a general rigidity of responding. Task-specific impairments in shifting response patterns have been previously reported in other situations, such as aging 43 and 65. However, there is an alternative explanation for these findings; since the object reversal learning was always followed by the spatial reversals, it is possible that with experience on the first task the monkeys got better at the reversal learning on the spatial task.
Consistent with our results, previous studies have shown that rhesus monkeys that have undergone early social deprivation perform adequately on simple discriminations [29]but show impairments in certain complex tasks 6, 7, 28 and 29. It should be noted that these results were obtained mostly from adult animals separated from their mothers at birth and reared in total isolation for 9–12 months. Although different from our nursery-rearing paradigm, some of the cognitive deficits found are similar, such as the cognitive inflexibility and specific information processing deficits, both of which are also observed in autistic children [53].
The two tasks in which we observed deficits in the NURSERY monkeys (acquisition of DNMS and object reversal learning) both involve a component of object discrimination. Nevertheless, since no deficits were found on the acquisition of the simple object discrimination or on the performance of the DNMS, the processing of the information about the visual characteristics of objects does not seem to be impaired. The two tasks on which NURSERY monkeys were impaired require the acquisition of a rule of performance (i.e., the acquisition of the non-matching principle in DNMS) or the learning of a change in an established rule of performance (as in the object reversal), both of which may be considered executive function. However, the deficits found cannot be attributed to difficulties in set- or rule-changing per se, since NURSERY and CONTROL monkeys performed equally well in spatial reversal. Thus, it appears that NURSERY animals show deficits on tasks involving new learning or executive function if object discriminations are involved.
What is the relationship of these cognitive deficits to the corpus callosum and cortical white matter changes observed in the NURSERY monkeys? Although we observed a significant correlation between the size of medial and caudal aspects of the CC, and the acquisition of the DNMS as well as the object reversal learning, these results need to be interpreted cautiously. The correlations are based on a small animal sample and there should be no presumption that the CC alterations found in NURSERY animals are directly responsible for the cognitive deficits exhibited. Indeed, previous reports have demonstrated that commissurotomized monkeys perform as well as controls in a simple object discrimination task [20], so it would be surprising if a decrease in CC area `caused' a selective deficit in executive function. Two alternative explanations for the correlations are: (a) that the change in CC area represents a more general loss of connectivity associated with impairment in complex cognitive processes or (b) that the NURSERY animals are developmentally delayed with both connectional and cognitive lags relative to CONTROLS. Infant macaques (less than 1 year of age) perform poorly in the DNMS task, which seems to be due to a functional immaturity of the neocortex, rather than to immaturity of the limbic structures at that stage of development 3 and 32. Therefore, the NURSERY animals' impairment in acquisition of DNMS could be due to alterations in the normal neocortical development, while those cognitive functions more dependent on hippocampal function, such as the delayed phase of the DNMS, were not affected (which is consistent with the absence of a decline in hippocampal volume). On the other hand, while the adult DNMS mastery is not achieved in rhesus monkeys until they are 2 years old, by 3 months of age they form visual discrimination habits as quickly as adult monkeys [4]. Therefore, nursery-rearing from 2–12 months may have altered more drastically neural systems still in development during that stage (such as those underlying acquisition of the DNMS) than those developed earlier (such as the ones underlying visual discrimination habit formation).
In summary, monkeys raised in a nursery from 2–12 months of age showed decreased midsagittal CC area when scanned at 18 months using MRI. The loss of cross-hemispheric projections was associated with a decrease in cortical white matter volume. NURSERY animals also had selective cognitive deficits which correlated with the changes found in the CC area. Animals that experienced 6 months of peer-grouping after the nursery rearing did not show improvements in relation to the animals that remained single-housed.


This work was supported by the Yerkes Regional Primate Research Center base grant No. RR-00165 awarded by the Comparative Medicine Program, National Center for Research Resources of the National Institutes of Health. Support was also provided by NIH grant PO1-AG0001. The authors thank Dr. R. Nisenbaum for statistical advice, and gratefully acknowledge Dr. T.R. Insel's help during this study and his critical review of the manuscript.


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