Last
updated 14 October 2012
Links are to pdf versions of the
papers, as available. Users are
responsible for compliance with copyright restrictions.
To download a pdf version click here.
References to the physics e-print
archive http://arxiv.org
are given where available. For preprints this is a primary reference; for other
work there may be slight differences between the e-print and conventional print
versions of the paper. Since almost all of my papers are now deposited on the
archive before journal publication, more recent papers are ordered by the date
of the archive submission.
145. Biophysics:
Searching for Principles. W
Bialek (Princeton
University Press, 2012).
144.
The simplest maximum entropy model for
collective behavior in a neural network. G Tkacik, O Marre, D Amodei, MJ Berry II & W Bialek,
arXiv.org:1207.6319 [q–bio.NC] (2012).
143.
Maximally informative Ňstimulus
energiesÓ in the analysis of neural responses to natural signals. K Rajan & W Bialek,
arXiv.org:1201.0321 [q–bio.NC] (2012).
142.
Positional information, in bits. JO Dubuis, G Tkacik, EF Wieschaus, T Gregor & W Bialek,
arXiv.org:1201.0198 [q–bio.MN] (2012).
141.
Optimizing information flow in small
genetic networks. III. A self--interacting gene. G Tkacik, AM Walczak & W Bialek, Phys
Rev E 85, 041903 (2012);
arXiv.org:1112.5026 [q–bio.MN] (2011).
140. Statistical mechanics for natural flocks of
birds. W Bialek, A Cavagna, I
Giardina, T Mora, E Silvestri, M Viale & A Walczak, Proc Natl Acad Sci (USA) 109,
4786-4791 (2012); arXiv.org:1107.0604 [physics.bio–ph] (2011).
139. When are correlations strong? F Azhar & W Bialek,
arXiv.org:1012.5987 [q–bio.NC] (2010).
138. Searching for simplicity: Approaches to the analysis of neurons
and behavior. GJ Stephens, LC
Osborne & W Bialek, Proc NaatŐl Acad Sci (USA) 108,
(Suppl 3) 15565-15571 (2011); arXiv.org:1012.3896 [q–bio.NC] (2010).
137. Are biological systems poised at
criticality? T Mora & W Bialek, J Stat Phys 144, 268-302 (2011); arXiv:1012.2242 [q–bio.QM] (2010).
136. Optimizing information flow in small
genetic networks. II: Feed-forward
interactions. AM Walczak, G Tkacik & W Bialek, Phys Rev E 81, 041905 (2010); arXiv:0912.5500
[q–bio.MN] (2009).
135. Spin glass models for networks of real
neurons. G Tkacik, E
Schneidman, MJ Berry II & W Bialek, arXiv:0912.5409 [q–bio.NC]
(2009).
134. Emergence of long timescales and
stereotyped behaviors in Caenorhabditis elegans. GJ Stephens, MB de Mesquita, WS
Ryu & W Bialek, Proc Nat'l Acad
Sci (USA) 108,
7286-7289 (2011).
For
a preliminary account, see The
emergence of stereotyped behaviors in C. elegans. GJ Stephens, WS Ryu & W Bialek,
arXiv:0912.5232 [q–bio.NC] (2009).
133. Maximum entropy models for antibody diversity. T Mora, AM Walczak, W Bialek & CG
Callan, Jr, Proc
Nat'l Acad Sci (USA) 107, 5405-5410 (2010); arXv:0912.5175 [q–bio.GN] (2009).
132. From modes to movement in C. elegans.
GJ Stephens, B Johnson-Kerner, W Bialek & WS Ryu, PLoS One 5, e13914 (2010); arXiv:0912.4760
[q–bio.NC] (2009).
131. Optimizing information flow in small
genetic networks. G
Tkacik, AM Walczak & W Bialek, Phys Rev E 80, 031920 (2009); arXiv:0903.4491
[q–bio.MN] (2009).
130. Thermodynamics of natural images. GJ Stephens, T Mora, G Tkacik & W
Bialek, Phys Rev Lett in press
(2012); arXiv:0806.2694 [q–bio.NC] (2008).
129. The neural basis for combinatorial coding
in a cortical population response. LC
Osborne, SE Palmer, SG Lisberger & W Bialek, J Neurosci 28, 13522–13531 (2008).
A
preliminary version is Combinatorial
coding in neural populations. arXiv:0803.3837 [q–bio.NC] (2008).
128. Can we fit all of the data? W Bialek, T Gregor, DW Tank & EF
Wieschaus, Cell
132, 17-18
(2008).
127. Statistical mechanics of letters in
words. GJ Stephens & W Bialek, Phys Rev E 81, 066119 (2010); arXiv:0801.0253
[q–bio.NC] (2008).
The
original title, preserved in the arXiv
version, was Toward a statistical mechanics of four letter words. This was ejected without review; the
editors claimed that it was Ňnot physics.Ó Some small changes to the text, some explanation, and a
change in title resulted in more serious consideration.
126. Rediscovering the power of pairwise
interactions. W Bialek & R
Ranganathan, arXiv:0712.4397 [q–bio.QM] (2007).
125. Cell biology: Networks, regulation,
pathways. G Tkacik & W
Bialek, in Encyclopedia
of Complexity and Systems Science, RA Meyers, ed, pp 719-741
(Springer-Verlag, Berlin, 2009); arXiv:0712.4385 [q–bio.MN] (2007).
124. Information
and fitness. SF Taylor, N
Tishby & W Bialek, arXiv:0712.4382 [q–bio.PE] (2007).
123. Efficient representation as a design
principles for neural coding and computation. W Bialek, RR de Ruyter van
Steveninck & N Tishby, arXiv:0712.4381 [q–bio.NC] (2007).
A
preliminary account appears in the Proceedings of the International Symposium
on Information Theory 2006, but this seems to be available only on CDs
distributed to meeting attendees (!).
122. Faster solutions of the inverse pairwise
Ising problem. T Broderick, M
Dudik, G Tkacik, RE Schapire & W Bialek, arXiv:0712.2437 [q–bio.QM]
(2007).
121. Diffusion, dimensionality and noise in
transcriptional regulation. G Tkacik & W Bialek, Phys Rev E 79, 051901 (2009); arXiv:0712.1852 [q–bio.MN] (2007).
See
also the accompanying commentary by R Metzler, Physics 2, 36 (2009).
120. Information capacity of genetic regulatory
elements. G Tkacik, CG Callan Jr & W Bialek, Phys Rev E 78, 011910 (2008); arXiv:0709.4209
[q–bio.MN] (2007).
119. Dimensionality and dynamics in the
behavior of C. elegans. GJ
Stephens, B Johnson-Kerner, W Bialek & WS Ryu, PLoS Comp Bio 4, e1000028 (2008); arXiv:0705:1548
[q–bio.OT] (2007).
118. Information flow and optimization in
transcriptional regulation. G
Tkacik, CG Callan Jr & W Bialek, Proc NatŐl Acad Sci (USA) 105, 12265-12270 (2008);
arXiv:0705.0313 [q–bio.MN] (2007).
117. Neural decision boundaries for maximal
information transmission. T
Sharpee & W Bialek, PLoS One 2, e646 (2007); q–bio.NC/0703046 (2007).
116. The role of input noise in transcriptional
regulation. G Tkacik, T Gregor & W Bialek, PLoS One 3, e2774 (2008); q–bio.MN/0701002
(2007).
115. Neural coding of a natural stimulus
ensemble: Information at sub-millisecond resolution. I Nemenman, GD Lewen,
W Bialek & RR de Ruyter van Steveninck, PLoS Comp Bio 4, e1000025 (2008); q–bio.NC/0612050 (2006).
114. Time course of precision in smooth pursuit
eye movements of monkeys. LC Osborne, SS Hohl, W Bialek & SG Lisberger,
J Neurosci
27, 2987-2998 (2007).
113. Ising models for networks of real neurons.
G Tkacik, E Schneidman, MJ Berry II & W Bialek, q–bio.NC/0611072
(2006).
112.
Probing
the limits to positional information. T Gregor, DW Tank, EF Wieschaus & W
Bialek, Cell 130, 153-164 (2007).
See
also the accompanying commentary on this and the next article by MC Gibson, Cell 130, 14-15 (2007).
111.
Stability
and nuclear dynamics of the Bicoid morphogen gradient. T Gregor, EF Wieschaus, AP McGregor, W
Bialek & DW Tank, Cell 130,
141-152 (2007).
110.
Cooperativity,
sensitivity and noise in biochemical signaling. W Bialek & S Setayeshgar, Phys Rev Lett 100, 258101
(2008); q–bio.MN/0601001 (2006).
109.
Weak
pairwise correlations imply strongly correlated network states in a neural
population.
E Schneidman, MJ Berry II, R Segev & W Bialek, Nature 440, 1007-1012 (2006);
q–bio.NC/0512013 (2005).
108.
Should you
believe that this coin is fair? W Bialek,
q–bio.NC/0508044 (2005).
107.
Synergy
from silence in a combinatorial neural code. E Schneidman, JL Puchalla, RA Harris, W
Bialek & MJ Berry II, q–bio.NC/0607017 (2006).
106.
Diffusion
and scaling during early embryonic pattern formation. T Gregor, W Bialek, RR de Ruyter van
Steveninck, DW Tank & EF Wieschaus, Proc NatŐl Acad Sci (USA) 102, 18403-18407 (2005).
105.
Information
based clustering. N Slonim, GS Atwal, G
Tkacik & W Bialek, Proc NatŐl Acad Sci (USA) 102, 18297-18302 (2005);
q–bio.QM/0511043. See also Supplementary material,
q–bio.QM/0511042 (2005).
104.
A
sensory source for motor variation. LC Osborne, SG Lisberger & W
Bialek, Nature
437,
412-416 (2005).
103.
Features
and dimensions: Motion estimation
in fly vision. W Bialek & RR de Ruyter van
Steveninck, q–bio/0505003 (2005).
102. Estimating mutual information and
multi–information in large networks. N Slonim, GS Atwal, G Tkacik & W
Bialek, cs.IT/0502017 (2005).
101. Physical
limits to biochemical signaling. W Bialek &
S Setayeshgar, Proc
NatŐl Acad Sci (USA) 102,
10040-10045 (2005); physics/0301001 (2003).
100. How
many clusters? An information theoretic perspective.
S Still & W Bialek, Neural Comp 16, 2483-2506 (2004);
physics/0301011 (2003).
99. Entropy and information in neural spike
trains: Progress on the sampling
problem.
I Nemenman, W Bialek & R de Ruyter van Steveninck, Phys Rev E 69, 056111 (2004); physics/0306063 (2003).
98. Time
course of information about motion
direction in visual area MT of macaque monkeys. LC Osborne, W Bialek & SG
Lisberger, J
Neurosci 24, 3210-3222 (2004).
97. Geometric
clustering using the information bottleneck method. S Still, W Bialek & L Bottou, in Advances in
Neural Information Processing 16, S Thrun, L Saul & B Schlkopf, eds,
pp 1165-1172 (MIT Press,
Cambridge, 2004).
96. Optimal
manifold representation of
data: An information theoretic perspective.
D Chigirev & W Bialek, in Advances in Neural Information Processing 16, S Thrun, L Saul &
B Schlkopf, eds, pp 161-168 (MIT Press, Cambridge, 2004).
95.
Ambiguous model learning made
unambiguous with 1/f priors.
GS Atwal & W Bialek, in Advances in
Neural Information Processing 16,
S Thrun, L Saul & B Schlkopf, eds, pp 1205-1212 (MIT Press,
Cambridge, 2004).
94.
Introductory science and
mathematics education for 21st century biologists. W Bialek & D Botstein, Science 308, 788-790 (2004).
93. Analyzing
neural responses to natural signals: Maximally informative dimensions. T Sharpee, NC Rust & W Bialek, Neural Comp 16, 223-250 (2004); physics/0212110 (2002).
For a preliminary account see Maximally informative dimensions:
Analyzing neural responses to natural signals, in Advances in Neural Information Processing 15,
S Becker, S Thrun & K Obermayer, eds, pp 261-268 (MIT Press, Cambridge,
2003); physics/0208057 (2002).
92. Spike
sorting in the frequency domain with overlap detection. D Rinberg, W
Bialek, H Davidowitz & N
Tishby, physics/0306056 (2003).
91. Synergy, redundancy, and independence
in population codes. E Schneidman, W Bialek & MJ Berry II, J Neurosci 23, 11539-11553 (2003).
90. Network information and connected
correlations. E Schneidman, S Still, MJ Berry II & W Bialek, Phys Rev Lett
91, 238701 (2003); physics/0307072
(2003).
89. The
information content of receptive fields. TL Adelman, W Bialek & RM
Olberg, Neuron
40, 822-833 (2003).
88. Computation in single neurons: Hodgkin and Huxley revisited. B
Agera y Arcas, AL Fairhall, & W Bialek, Neural Comp 15, 1715-1749 (2003); physics/0212113
(2002).
For a preliminary
account see What can a single neuron compute?, in Advances in Neural Information Processing
13, TK Leen, TG Dietterich & V Tresp, eds, pp 75-81 (MIT Press, Cambridge,
2001).
87. An information theoretic approach to
the functional classification of neurons. E Schneidman, W Bialek, & MJ
Berry II, in Advances
in Neural Information Processing 15, S Becker, S Thrun & K Obermayer,
eds, pp 197-204 (MIT Press, Cambridge, 2003); physics/0212114 (2002).
86. Adaptive spike coding. A Fairhall &
W Bialek, in The
Handbook of Brain Theory and Neural Networks, Second Edition, MA Arbib, ed,
pp 90-94 (MIT Press, Cambridge, 2002).
85. Statistical
properties of spike trains: Universal and stimulus-dependent aspects. N
Brenner, O Agam, W Bialek, & RR de Ruyter van Steveninck, Phys Rev E 66, 031907 (2002); physics/9902061 (1999).
For a preliminary account see Universal
statistical behavior of neural spike trains,
Phys Rev Lett.
81, 4000-4003 (1998); physics/9801026 (1998).
84. Thinking
about the brain. W Bialek, in Physics of
Biomolecules and Cells: Les Houches Session LXXV, H Flyvbjerg, F Jlicher,
P Ormos, & F David, eds, pp 485-577 (EDP Sciences, Les Ulis;
Springer-Verlag, Berlin, 2002); physics/0205030 (2002).
83. Entropy
and inference, revisited. I Nemenman, F Shafee, & W Bialek, in Advances in
Neural Information Processing 14, TG Dietterich, S Becker & Z
Ghahramani, eds, pp 471-478 (MIT Press, Cambridge, 2002); physics/0108025
(2001).
82. Spike
timing and the coding of naturalistic sounds in a central auditory area of songbirds.
BD Wright, K Sen, W Bialek, & AJ Doupe, in Advances in Neural Information Processing 14, TG Dietterich, S Becker & Z Ghahramani, eds, pp
309-316 (MIT Press, Cambridge, 2002); physics/0201027 (2002).
81.
Timing and counting precision in the
blowfly visual system. R de Ruyter van Steveninck & W Bialek, in Models of Neural Networks IV: Early Vision and Attention, JL van Hemmen, J Cowan & E
Domany, eds, pp 313-365 (Springer-Verlag, Berlin, 2002); physics/0202014
(2002).
80. Occam factors and model-independent
Bayesian learning of continuous distributions. I Nemenman & W Bialek, Phys Rev E 65, 026137 (2002); cond mat/0009165 (2000).
For a preliminary
account see Learning continuous distributions: Simulations with a field
theoretic prior, in Advances in Neural Information Processing 13, TK Leen, TG
Dietterich & V Tresp, eds, pp 287-293 (MIT Press, Cambridge, 2001).
79. Complexity
through nonextensivity. W Bialek, I Nemenman & N Tishby, Physica A 302, 89-99
(2001); physics/0103076 (2001).
78. Efficiency
and ambiguity in an adaptive neural code. AL Fairhall, GD Lewen, W
Bialek & RR de Ruyter van Steveninck, Nature 412, 787-792 (2001).
See also the
accompanying commentary by P. Reinagel, Nature 412, 776-777 (2001). For a preliminary account see Multiple timescales
of adaptation in a neural code, in Advances in Neural Information Processing 13,
TK Leen, TG Dietterich & V Tresp, eds, pp 124-130 (MIT Press, Cambridge,
2001).
77. Neural
coding of naturalistic motion stimuli. GD
Lewen, W Bialek & RR de Ruyter van Steveninck, Network 12, 317-329 (2001); physics/0103088 (2001).
76. Predictability,
complexity and learning. W Bialek, I Nemenman & N Tishby, Neural Comp 13, 2409-2463 (2001); physics/0007070 (2000).
For a preliminary
account see Predictive
information, W Bialek & N Tishby;
cond-mat/9902341.
75. Universality and individuality in a
neural code. E
Schneidman, N Brenner, N Tishby, RR de Ruyter van
Steveninck & W Bialek, in Advances in
Neural Information Processing 13, TK Leen, TG Dietterich & V Tresp,eds,
pp 159-165 (MIT Press, Cambridge, 2001); physics/0005043 (2000).
74. Stability
and noise in biochemical switches. W Bialek, in Advances in Neural Information Processing
13, TK Leen, TG Dietterich & V Tresp, eds, pp 103-109 (MIT Press,
Cambridge, 2001); cond-mat/0005235 (2000).
73. Real
time encoding of motion: Answerable questions and questionable answers from the
fly's visual system. R de
Ruyter van Steveninck, A Borst & W Bialek, in Processing Visual Motion in the Real World:
A Survey of Computational, Neural and Ecological Constraints, JM Zanker
& J Zeil, eds, pp 279-306 (Springer-Verlag, Berlin, 2001); physics/0004060
(2000).
72. Adaptive
rescaling optimizes information transmission.
N Brenner, W Bialek & R de Ruyter van Steveninck, Neuron 26, 695-702 (2000).
See also the
accompanying commentary by M DeWeese, Neuron 26, 546-548 (2000).
71. Synergy
in a neural code. N Brenner,
SP Strong, R Koberle, W Bialek & RR de Ruyter van Steveninck, Neural Comp 12, 1531-1552 (2000); physics/9902067
(1999).
70. Potenialit e limitazioni nella misura
della transmission dell'informazione neuronale.
W Bialek, in Frontiere Della Vita, Vol. III: Sistemi Intelligenti, pp 617-629
(Instituto della Enciclopedia Italiana, 1999).
From an English manuscript,
Prospects and pitfalls in the measurement of neural information
transmission. English edition: Frontiers of Life, Vol III: Intelligent Systems (Academic
Press, San Diego, 2002).
69. The
information bottleneck method.
N Tishby, FC Pereira, & W Bialek, in Proceedings of the 37th Annual Allerton
Conference on Communication, Control and Computing, B Hajek & RS
Sreenivas, eds, pp 368-377 (University of Illinois, 1999); physics/0004057 (2000).
68. Adaptation
and optimal chemotactic strategy for E. Coli.
SP Strong, B Freedman, W Bialek & R Koberle, Phys Rev E 57, 4604-4617 (1998); adap-org/9706001 (1997).
67. On
the application of information theory to neural spike trains. SP Strong, RR de Ruyter van
Steveninck, W Bialek & R Koberle, in Pacific Symposium on Biocomputing `98, RB Altman, AK Dunker, L
Hunter & TE Klein, eds, pp 621-632 (World Scientific, Singapore, 1998).
66. Entropy
and information in neural spike trains. SP Strong, R Koberle, RR de Ruyter van Steveninck & W
Bialek, Phys
Rev Lett 80, 197-200 (1998); cond-mat/9603127
(1996).
65.
Spikes: Exploring the Neural Code. F Rieke, D Warland, R de Ruyter van
Steveninck & W Bialek (MIT
Press, Cambridge, 1997). Introductory
chapter
Reviews
include: A King, The London Times Higher Education Supplement 17
October 1997, p. 35; A Zador, Science 277, 772 (1997); LF Abbott, Neuron 19, 5 (1997); M Abeles, Trends Neurosci. 20, 496
(1997).
64. Statistical mechanics and sensory
signal processing. W Bialek, in Physics of
Biological Systems: From Molecules
to Species, H Flyvbjerg, J Hertz, MH Jensen, OG Mouristen & K Sneppen,
eds, pp 252-280 (Springer-Verlag, Berlin, 1997).
63. Reproducibility
and variability in neural spike trains. RR de Ruyter van Steveninck, GD Lewen, SP Strong, R Koberle
& W Bialek, Science
275,
1805-1808 (1997).
62. Adaptation of retinal processing to image
contrast and spatial scale. S
Smirnakis, MJ Berry II, DK Warland, W Bialek & M Meister, Nature 386, 69-73
(1997).
61. Adaptive movement computation by the
blowfy visual system. RR de Ruyter
van Steveninck, W Bialek, M Potters, RH Carlson & GD Lewen, in Natural and Artificial Parallel Computation: Proceedings of the Fifth
NEC Research Symnposium, DL Waltz, ed, 21-41 (SIAM, Philadelphia, 1996).
60. Field
theories for learning probability distributions. W Bialek, CG
Callan & SP Strong, Phys Rev Lett 77, 4693-4697 (1996); cond-mat/9607180 (1996).
59. Optimality and adaptation in motion
estimation by the blowfly visual system. RR de Ruyter van Steveninck & W Bialek, Proceedings of
the IEEE 22nd Annual Northeast
Bioengineering Conference,
40-41 (1996).
58. Naturalistic
stimuli increase the rate and efficiency of information transmission by primary
auditory neurons. F Rieke, DA
Bodnar & W Bialek, Proc R Soc Lond Ser B 262,
259-265 (1995).
57. Reliability and statistical efficiency
of a blowfly movement-sensitive neuron. R de Ruyter van Steveninck & W Bialek, Phil Trans R Soc
Lond Ser B 348,
321-340 (1995).
For a preliminary
account see Statistical
reliability of a blowfly movement-sensitive neuron,
in Advances in Neural Information Processing 4,
J Moody, SJ Hanson & RP Lippman, eds pp 27-34, (Morgan Kaufmann, San Mateo
CA, 1992).
56. Random switching and optimal processing
in the perception of ambiguous signals. W Bialek & M DeWeese, Phys Rev Lett 74, 3077-3080 (1995).
55. Information flow in sensory neurons. M DeWeese & W Bialek, Il Nuovo Cimento 17D, 733-741 (1995).
54. Statistical
adaptation and optimal estimation in movement computation by the blowfly visual
system. RR de Ruyter van
Steveninck, W Bialek, M Potters & RH Carlson, in Proc IEEE Conf Sys Man Cybern, 302-307
(1994).
53. Statistical mechanics and visual signal processing. M Potters & W Bialek, J Phys I France 4, 1755-1775 (1994); cond-mat/9401072 (1994).
52. Statistics of natural images: Scaling
in the woods. DL Ruderman
& W Bialek, Phys
Rev Lett 73, 814-817 (1994).
For a preliminary
account see Advances
in Neural Information Processing 6, JD Cowan, G Tesauro & J Alspector,
eds, pp 551-558 (Morgan Kaufmann, San Mateo CA, 1994).
51. Properties and origins of protein secondary structure. N Socci, W Bialek & JN Onuchic, Phys Rev E 49, 3400-3443 (1994); cond-mat/9402010 (1994).
50. Visual computation: A fly's eye view. W Bialek, M Potters, DL Ruderman & R de Ruyter van Steveninck, in Cognitive Processing for Vision and Voice, Proceedings of the Fourth NEC Research Symposium, T Ishiguro, ed, pp 7-26, (SIAM, Philadelphia, 1993).
49. Non-phase-locked auditory cells and
envelope detection. F Rieke, W
Yamada, E Lewis & W Bialek, in Analysis and Modeling of Neural Systems 2, F
Eeckman, ed, pp 255-263 (Kluwer Academic, 1993).
48. Bits
and brains: Information flow in the nervous system. W Bialek, M DeWeese, F Rieke & D
Warland, Physica
A 200, 581-593 (1993).
47. Nonperturbative approach to non-Condon
effects: Must a nonadiabatic
transition always occur at the potential surface crossing? RF Goldstein, S Franzen & W Bialek, J Phys Chem 97, 11168-11174
(1993).
46. Virtual
transitions in nonadiabatic condensed phase reactions. JS Joseph & W Bialek, J Phys Chem 97, 3245-3256 (1993).
45. Coding efficiency and information rates
in sensory neurons. F Rieke, D
Warland & W Bialek, Europhys Lett 22, 151-156, (1993).
For a preliminary
account see Measuring the coding efficiency of sensory neurons, in Analysis and Modeling of Neural Systems 2, F
Eeckman, ed, pp 29-38 (Kluwer Academic, 1993).
44. Statistical mechanics for a network of
spiking neurons. L Kruglyak &
W Bialek, Neural
Comp 5, 21-31 (1993).
43.
Princeton Lectures on Biophysics. W Bialek, ed (World Scientific,
Singapore, 1992).
42. Optimal signal processing in the
nervous system. W Bialek, in [43],
pp 321-401 (1992).
See also Optimal real-time signal
processing in the nervous system, in Analysis and Modeling of Neural Systems 2, F Eeckman, ed, pp 5-28 (Kluwer Academic, 1993).
41. Reliability and information
transmission in spiking neurons.
W Bialek & F Rieke, Trends Neurosci 15, 428-434
(1992).
40. Real-time coding of complex sounds in
the auditory nerve. F Rieke, W
Yamada, K Moortgat, ER Lewis & W Bialek, in Auditory Physiology and Perception:
Proceedings of the 8th International Conference on Hearing, Y Cazals, L
Demany, & K Horner, eds, pp 315-322 (Pergamon, 1992).
39. Seeing beyond the Nyquist limit. DL Ruderman & W Bialek, Neural Comp 4, 682-690 (1992).
Reprinted in Neural Codes and
Distributed Representations: Foundations of Neural Computation, LF Abbott
& TJ Sejnowski, eds (MIT Press, Cambridge, 1999).
38. A
new look at the primary charge separation in bacterial photosynthesis. SS Skourtis, AJR DaSilva, W Bialek
& JN Onuchic, J Phys Chem 96, 8034-8041 (1992).
37. Vibrationally enhanced tunneling as a
mechanism for enzymatic hydrogen transfer. WJ Bruno & W Bialek, Biophys J 63, 689-699 (1992).
36. Virtual intermediates in photosynthetic
electron transfer. JS Joseph &
W Bialek, Biophys
J 63, 397-411 (1992).
35. Bleaching
of the bacteriochlorophyll monomer: Can absorption kinetics distinguish virtual
from two-step transfer? JS Joseph, WJ Bruno & W Bialek, J Phys Chem 95, 6242-6247 (1991).
34. Reading a neural code. W Bialek, F Rieke, RR de Ruyter van
Steveninck & D Warland, Science 252, 1854-1857
(1991).
Reprinted in Biology and Computation: A Physicist's Choice, H Gutfreund & G Toulouse, eds
(World Scientific, Signapore, 1994). For a preliminary account see Advances in Neural Information Processing 2, D
Touretzky, ed, pp 36-43 (Morgan Kaufmann, San Mateo CA, 1990).
33. Reading between the spikes in the
cricket cercal afferent system. D
Warland, M Landolfa, JP Miller & W Bialek, in Analysis and Modeling of Neural Systems, F Eeckman, ed, pp 327-333
(Kluwer Academic, 1991).
32. Optimal sampling of natural images: A
design principle for the visual system? W
Bialek, DL Ruderman & A Zee, in Advances in Neural Information Processing 3, R Lippman, J Moody
& D Touretzky, eds, pp 363-369 (Morgan Kaufmann, San Mateo CA, 1991).
31. Analog computation at a critical point:
A novel function for neuronal oscillations? L Kruglyak & W Bialek, in Advances in Neural Information Processing 3, R Lippman, J Moody
& D Touretzky, eds, pp 137-143 (Morgan Kaufmann, San Mateo CA, 1991).
30. Optimal
filtering in the salamander retina. F
Rieke, WG Owen, & W Bialek, in Advances in Neural Information Processing 3, R
Lippman, J Moody & D Touretzky, eds, pp 377-383 (Morgan Kaufmann, San Mateo
CA, 1991).
See also Analysis and
Modeling of Neural Systems, F Eeckman, ed, pp 231-237 (Kluwer Academic,
1991).
29. Theoretical physics meets experimental
neurobiology. W Bialek, in 1989 Lectures in
Complex Systems, SFI Studies in the Sciences of Complexity, Lect. Vol. II,
E Jen, ed, pp 513-595
(Addison-Wesley, Menlo Park CA, 1990).
28. Biomolecular dynamics—Quantum or
classical?: Results for photosynthetic electron transfer. JN Onuchic, RF Goldstein & W
Bialek, in Perspectives in Photosynthesis: Proceedings
of the 22nd Jerusalem Symposium on Quantum Chemistry and Biochemistry, J
Jortner & B Pullman, eds, pp 185-210 (Kluwer Academic, Dordrecht, 1990).
27. Temporal
filtering in retinal bipolar cells: Elements of an optimal computation? W Bialek & WG Owen, Biophys J 58,
1227-1233 (1990).
26. Non–Boltzmann dynamics in
networks of spiking neurons. MC
Crair & W Bialek, in Advances in
Neural Information Processing 2, D. Touretzky, ed, pp 109-116 (Morgan
Kaufmann, San Mateo CA, 1990).
25. Coding
and computation with neural spike trains. W Bialek & A Zee, J Stat Phys 59, 103-115 (1990).
24. Quantum and classical dynamics in
biochemical reactions. W Bialek,
WJ Bruno, JS Joseph & JN Onuchic, Photosyn Res 22, 17-25 (1989).
23. Optimal performance of a
feed–forward network at statistical discrimination tasks. W Bialek, R Scalettar & A
Zee, J Stat
Phys 57,
141-156 (1989).
22. Understanding
the efficiency of human perception.
W Bialek & A Zee, Phys Rev Lett 61,
1512-1515 (1988).
21. Real–time performance of a
movement sensitive neuron in the blowfly visual system: Coding and information
transfer in short spike sequences.
R de Ruyter van Steveninck & W Bialek, Proc R Soc London Ser B 234,
379-414 (1988).
20. Protein dynamics and reaction rates:
Mode–specific chemistry in large molecules?. W Bialek & JN Onuchic, Proc
NatŐl Acad Sci (USA) 85, 5908-5912 (1988).
19. Physical
limits to sensation and perception.
W Bialek, Ann.
Rev Biophys Biophys Chem 16, 455-478 (1987).
18. Statistical
mechanics and invariant perception.
W Bialek & A Zee, Phys Rev Lett 58, 741-744
(1987).
17. Tunneling
spectroscopy of a macroscopic variable. W
Bialek, S Chakravarty & S Kivelson, Phys Rev B 35, 120-123 (1987).
16. Simple
models for the dynamics of biomolecules: How far can we go? W Bialek, RF Goldstein & S
Kivelson, in Structure,
Dynamics and Function of Biomolecules: The First EBSA Workshop, A
Ehrenberg, R Rigler, A Grslund & LJ Nilsson, eds, pp 65-69
(Springer-Verlag, Berlin, 1987).
15. Protein dynamics, tunneling, and all
that. W Bialek & RF
Goldstein, Phys
Scr 34, 273-282 (1986).
14. Protein dynamics and reaction rates:
Are simple models useful? RF
Goldstein & W Bialek, Comments Mol Cell Biophys 3, 407-438 (1986).
13. Macroscopic
T non-conservation: Prospects for a new experiment. W Bialek, J Moody & F Wilczek, Phys Rev Lett 56, 1623-1626 (1986).
12.
The Vertebrate Inner Ear.
ER Lewis, EL Leverenz & W Bialek (CRC Press, Boca Raton,
1985).
11. Quantum noise and the threshold of
hearing. W Bialek & A
Schweitzer, Phys
Rev Lett 54, 725-728 (1985). Erratum 56, 996 (1986).
10. Do vibrational spectroscopies uniquely
describe protein dynamics?: The case for myoglobin. W Bialek & RF Goldstein, Biophys J 48, 1027-1044 (1985).
For a preliminary
account see Protein vibrations can markedly affect reaction kinetics:
Interpretation of Myoglobin–CO recombination, in Protein Structure: Molecular and Electronic
Reactivity, RH Austin, E Buhks, B Chance, D DeVault, PL Dutton, H Frauenfelder
& VI Gol'danskii, eds, pp 187-199 (Springer-Verlag, Berlin, 1987).
9. Quantum limits to oscillator stability:
Theory and experiments on an acoustic emission from the human ear. W Bialek & HP Wit, Phys Lett A 104,
173-178 (1984).
8. Phonon super-radiance. W Bialek, Phys Lett A 103, 349-352 (1984).
7. Quantum
noise and active feedback. W
Bialek, Phys
Rev D 28, 2096-2098 (1983).
6. Vibronically coupled two-level systems:
Radiationless transitions in the slow regime. RF Goldstein & W Bialek, Phys Rev B 27, 7431-7439 (1983).
5.
Quantum effects in the dynamics of biological
systems. W Bialek, Doctoral
Dissertation (University of California, Berkeley, 1983).
4. Thermal and quantum noise in the inner
ear. W Bialek, in Mechanics of Hearing, E de Boer & MA
Viergever, eds, pp 185-192 (Nijhof, the Hague, 1983).
3. Thermal noise and active processes in the inner ear: Relating theory
to experiment. W Bialek, in Hearing: Physiological Bases and Psychophysics,
R Klinke & R Hartmann, eds, pp 51-57 (Springer-Verlag, Berlin, 1983).
2.
Kinetics and mechanism of force production
in muscle. W Bialek,
Undergraduate Honors Thesis (University of California, Berkeley, 1979).
1. Contraction of glycerinated muscle fibers
as a function of the ATP concentration. R Cooke & W Bialek, Biophys J 28,
241-258 (1979).