TY - JOUR
T1 - Control of time-dependent biological processes by temporally patterned input
AU - Brezina, Vladimir
AU - Orekhova, Irina V.
AU - Weiss, Klaudiusz R.
PY - 1997/9/16
Y1 - 1997/9/16
N2 - Temporal patterning of biological variables, in the form of oscillations and rhythms on many time scales, is ubiquitous. Altering the temporal pattern of an input variable greatly affects the output of many biological processes. We develop here a conceptual framework for a quantitative understanding of such pattern dependence, focusing particularly on nonlinear, saturable, time- dependent processes that abound in biophysics, biochemistry, and physiology. We show theoretically that pattern dependence is governed by the nonlinearity of the input-output transformation as well as its time constant. As a result, only patterns on certain time scales permit the expression of pattern dependence, and processes with different time constants can respond preferentially to different patterns. This has implications for temporal coding and decoding, and allows differential control of processes through pattern. We show how pattern dependence can be quantitatively predicted using only information from steady, unpatterned input. To apply our ideas, we analyze, in on experimental example, how muscle contraction depends on the pattern of motorneuron firing.
AB - Temporal patterning of biological variables, in the form of oscillations and rhythms on many time scales, is ubiquitous. Altering the temporal pattern of an input variable greatly affects the output of many biological processes. We develop here a conceptual framework for a quantitative understanding of such pattern dependence, focusing particularly on nonlinear, saturable, time- dependent processes that abound in biophysics, biochemistry, and physiology. We show theoretically that pattern dependence is governed by the nonlinearity of the input-output transformation as well as its time constant. As a result, only patterns on certain time scales permit the expression of pattern dependence, and processes with different time constants can respond preferentially to different patterns. This has implications for temporal coding and decoding, and allows differential control of processes through pattern. We show how pattern dependence can be quantitatively predicted using only information from steady, unpatterned input. To apply our ideas, we analyze, in on experimental example, how muscle contraction depends on the pattern of motorneuron firing.
UR - http://www.scopus.com/inward/record.url?scp=0030922881&partnerID=8YFLogxK
U2 - 10.1073/pnas.94.19.10444
DO - 10.1073/pnas.94.19.10444
M3 - Article
C2 - 9294230
AN - SCOPUS:0030922881
SN - 0027-8424
VL - 94
SP - 10444
EP - 10449
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 19
ER -