Biosensors & Bioelectronics 16 (2001) 527 – 533 Modulation of neural network activity by patterning John C. Chang a,1 , Gregory J. Brewer b,2 , Bruce C. Wheeler a, * a Department of Electrical and Computer Engineering, Beckman Institute, Uniersity of Illinois at Urbana -Champaign, 405 N. Mathews Aenue, Urbana, IL 61801, USA b Departments of Neurology and Medical Microbiology and Immunology, Southern Illinois Uniersity School of Medicine, PO Box 19626, Springfield, IL 62794 -9626, USA Abstract Using neuronal cultures on microelectrode arrays, researchers have shown that recordable electrical activity can be influenced by chemicals in the culture environment, thus demonstrating potential applicability to biosensors or drug screening. Since practical success requires the design of robust networks with repeatable, reliable responses understanding the sources of variation is important. In this report, we used lithographic technologies to confine neurons to highly defined patterns (40 m wide stripes); in turn these patterns gave us a measure of control over the local density of neurons (100–500 cells/mm 2 ). We found that the apparent electrical activity of the network, as measured by the fraction of electrodes from which signals were recordable, increases 8 – 10-fold with greater local density. Also, average-firing rates of the active neurons increased 3 – 5-fold. We conclude that patterned networks offer one means of controlling and enhancing the responsiveness of cultured neural networks. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Patterning; Recording; Hippocampal; Network activity www.elsevier.com/locate/bios 1. Introduction Recent research has shown that neurons can be grown in culture so as to respond in a dose dependent manner to chemicals by changing their firing pattern (Gross et al., 1997; Morefield et al., 2000). This obser- vation has led to the suggestion that neural networks can serve as chemical sensors. To fully exploit the concept of a neuron-based biosensor, however, the variables controlling the sensor behavior must be thor- oughly explored. Variables such as cell-type, cell den- sity, cell plasticity, and cell interaction should be reasonably controlled to manipulate important sensor properties, such as robustness and repeatability. To control robustness, one could alter the cell density as it is known that hippocampal neurons survive better at high densities, because they secrete a greater amount of glutamine (Watanabe et al., 1998). Alternatively, glia can modulate the network baseline activity through the glutamine that they supply to the neurons (Huelsmann et al., 2000), or different cell-types may be selected to respond better to a specific stimulus (Morefield et al., 2000). However, methods for controlling the sensitivity and repeatability of the sensor seem less clear, because sensitivity to chemicals changes with the area of growth (Gross et al., 1997), spontaneous activity pattern changes with network size (Gross, 1994), and response changes with exposure history of the sensor (Gross et al., 1997). While these results are strong indications that neuronal cultures can serve as biosensors, they also underscore the need for further understanding of the underlying biological mechanisms, e.g., development and plasticity, in order to create robust, reliable and repeatable sensors. In order to further our understanding of the depen- dence of neural activity on experimental characteristics, we are exploring the potential for the use of networks grown in patterns. Previously, we have shown that patterned hippocampal neurons develop electrical activ- ity (Chang et al., 2000). In this report, we have com- * Corresponding author. Tel.: +1-217-333-3236; fax: +1-217-244- 5180. E-mail addresses: jcchang@uiuc.edu (J.C. Chang), gbrewer@siumed.edu (G.J. Brewer), bwheeler@uiuc.edu (B.C. Wheeler). 1 Tel.: +1-217-244-2692. 2 Tel.: +1-217-785-5230; fax: +1-217-524-3227. 0956-5663/01/$ - see front matter © 2001 Elsevier Science B.V. All rights reserved. PII:S0956-5663(01)00166-X