autotrophic flagellates (2–20 mm), consumed by micro and mesozooplankton;
picoplankton (0.2–2 mm), consumed by heterotrophic nanoflagellates; and inedible
phytoplankton .20 mm. The uptake of nutrients (NO
3
, NH
4
and PO
4
) have been
decoupled from the carbon assimilation processes by including dynamic nutrient
kinetics
22
, whereby nutrient uptake is dependent on both the level of intercellular storage
and external nutrient concentrations. The microbial food web contains bacteria,
heterotrophic flagellates and microzooplankton, each with dynamically varying C:N:P
ratios and is described in ref. 23. Bacteria consume DOC, decompose detritus and can
compete for inorganic nutrients with phytoplankton. Heterotrophic flagellates feed on
bacteria and picoplankton and are consumed by microzooplankton and
mesozooplankton. Microzooplankton feed on diatoms, autotrophic and heterotrophic
flagellates and are consumed by mesozooplankton. Mesozooplankton feed on diatoms,
autotrophic flagellates and microzooplankton
24
. All three grazer groups are cannibalistic.
Simulations were made with the ERSEM parameter sets used in ref. 15, for the Humber
plume region of the North Sea. The model was forced by heat fluxes calculated from
meteorological data observed at Dublin. Although data for Dublin are not from the North
Sea, Dublin lies directly in the path of weather systems which commonly move from the
Gulf Stream to the North Sea.
Received 25 September 2001; accepted 24 January 2002.
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Acknowledgements
We wish to thank J. Stephens and J. Dearman for assisting with the calculations. B. Clarke
provided statistical advice. A.H.T. is a Fellow of the Sir Alister Hardy Foundation for
Ocean Science, which provided the plankton data. This work is part of the Core Strategic
Programme of Plymouth Marine Laboratory.
Competing interests statement
The authors declare that they have no competing financial interests.
Correspondence and requests for materials should be addressed to A.H.T.
(e-mail: aht@pml.ac.uk).
..............................................................
Direct visuomotor transformations
for reaching
Christopher A. Buneo, Murray R. Jarvis, Aaron P. Batista*
& Richard A. Andersen
Division of Biology, California Institute of Technology, Mail Code 216-76,
Pasadena, California 91125, USA
.............................................................................................................................................................................
The posterior parietal cortex (PPC) is thought to have a function
in the sensorimotor transformations that underlie visually
guided reaching, as damage to the PPC can result in difficulty
reaching to visual targets in the absence of specific visual or
motor deficits
1
. This function is supported by findings that PPC
neurons in monkeys are modulated by the direction of hand
movement, as well as by visual, eye position and limb position
signals
2–9
. The PPC could transform visual target locations from
retinal coordinates to hand-centred coordinates by combining
sensory signals in a serial manner to yield a body-centred
representation of target location
10–12
, and then subtracting the
body-centred location of the hand. We report here that in dorsal
area 5 of the PPC, remembered target locations are coded with
respect to both the eye and hand. This suggests that the PPC
transforms target locations directly between these two reference
frames. Data obtained in the adjacent parietal reach region (PRR)
indicate that this transformation may be achieved by vectorially
subtracting hand location from target location, with both
locations represented in eye-centred coordinates.
The problem that we address here is shown in Fig. 1a. Although
the execution of movement requires the specification of a detailed
pattern of inputs to the muscles, movement planning is believed to
involve the computation of higher level movement parameters, such
as the direction and/or distance that the hand must move to reach
the target (vector M)
10
. This is due to the fact that movement goals,
as well as evidence of our success in achieving these goals, are largely
expressed in high level terms, that is, as visually perceived discre-
pancies between the position of the hand and target or deviations
from a desired path
13
. Hereafter we use the term ‘target position in
hand coordinates’ to describe vector M in Fig. 1a, although the
terms ‘movement vector’ and ‘motor error’ could also be used. This
information could be derived by subtracting the sensed location of
the hand (vector H) from the sensed location of the target (vector
T), as long as hand position and target position are coded in a
common frame of reference. However, although target position
appears to be coded in eye-centred (retinal) coordinates in the early
stages of reach planning
14
, hand position is derived from both visual
and proprioceptive signals, and can conceivably be coded in eye-
centred coordinates, body centred coordinates (that is, with respect
to the torso), or both. It is unclear therefore whether the operation
shown in Fig. 1a is achieved by subtracting the position of the hand
from the position of the target directly, using eye-centred coordi-
nates (Fig. 1a, b), or by transforming target locations from eye- to
head- to body-centred coordinates, and then subtracting the body-
centred position of the hand
10,11
(Fig. 1c).
We have approached this problem by analysing the reach-related
activity of neurons in the PPC, while varying target position, hand
position and gaze direction. Single cell recordings were obtained
from area 5 (Fig. 2a, b), a subdivision of the PPC that projects
directly to cortical and subcortical motor structures
15–17
. In an
initial experiment, 89 neurons from two monkeys were studied
under four experimental conditions (Fig. 2c). In two conditions,
gaze was held constant at the centre position of a vertically oriented
* Present address: Howard Hughes Medical Institute, and Department of Neurobiology,
Stanford University School of Medicine, Fairchild Building, Room D209, Stanford, California 94305, USA
letters to nature
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