Drake, Roger A. (2004) Parameters for Modeling Behavioral Effects of Focal Stimulation. In: 11th Joint Symposium on Neural Computation, 15 May 2004, University Of Southern California. (Unpublished) http://resolver.caltech.edu/CaltechJSNC:2004.poster006
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A major research method in neuroscience is manipulation of relative regional activation by focal stimulation, followed by the observation of behavioral effects. Electrical methods include direct current stimulation (Antal et al., 2004), and transcranial magnetic stimulation (Fierro et al., 2000). Perceptually-based methods include tachistoscopic (Zarate et al., 2000), partially-obscured contact lens (Levick et al., 1993), haptic (Bassel & Schiff, 2001), auditory (Drake & Sobrero, 1987), or motor (McCourt et al., 2001; Schiff et al., 1998) orientation of attention. Biofeedback is also effective for the voluntary control of regionalcerebral activation (Pulvermuller, Mohr, Schleichert, & Veit, 2000; Rosenfeld,Cha, Blair, & Gotlib,1995; Schwartz, Davidson, & Pugash, 1976). A computational model linking these manipulations with the resulting cognitive and affective behavior needs to account for at least the following three parameters: a) an individual difference in variability of functions among regions (Chiarello, Kacinik, Manowitz, Otto, & Leonard, 2004; Hellige, Bloch, Cowin, Eng, Eviatar, & Sergent,1994; Neubauer, Grabner, Freudenthaler, Beckmann, & Guthke, 2004), b) an individual difference in reactivity to the manipulation (Wexler, Schwartz, Warrenburg, Servis, & Tarlatzis, 1986; Wheeler, Davidson, & Tomarken, 1993), and c) the effective strength of the manipulation. These parameters will probably be multiplicative, but perhaps with logarithmic or power factors. A tentative computational formula is: dQ = a[1 + b(c)] where dQ is delta or differential change in behavior as a result of the manipulation. An example of such a change is increase or decrease in risk taking because of manipulated stimulation of a region (Drake, 1985). This phenomenon is replicated in lesion studies (Miller & Milner, 1985), but the datafitting power of the formula and the relative contribution of each variable await parametric empirical testing. Support for this submission was provided in part by a grant from the National Institute on Drug Abuse to the USC Institute for Prevention Research (P50-DA16094).
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|Deposited On:||07 Jun 2004|
|Last Modified:||24 Oct 2011 21:36|
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