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The role of the influencer in innovation adoption
Published in Sergio Barile, Raul Espejo, Igor Perko, Marialuisa Saviano, Francesco Caputo, Cybernetics and Systems, 2018
Beatrice Orlando, Antonio Renzi, Giuseppe Sancetta, Maria Antonella Ferri
Technically, the waterfall effect is a visual illusion created by watching a moving object such as flowing water, then looking at a stationary object (Barlow, 1972): neurons coding a particular movement reduce their responses with time of exposure to a constantly moving stimulus; this is neural adaptation. Neural adaptation also reduces the spontaneous, baseline activity of these same neurons when responding to a stationary stimulus. We argue that digital users mostly rely on their intuitive thinking (Kahneman, 2011) and process less information to make a decision. So, influencers can steer the social narrative and lead to fast innovation adoptions by users, in reason of an imitation mechanism. We refer to imitation as that semi-unconscious mechanism, implemented to increase survival chances. In particular, we consider the influencer as the innovator, which initial behavior is able to trigger further and later adoptions by an indefinite number of users. From the initial community, or the target reached by the influencer, the effect spreads in other communities, thanks to the action of followers.
Spatial Orientation
Published in Pamela S. Tsang, Michael A. Vidulich, Principles and Practice of Aviation Psychology, 2002
This simple mechanical explanation shows how the semicircular canals correctly indicate head velocity for brief head movements, but decay to zero for sustained constant velocity turns. For extremely short disturbances, the cupula displacement is actually proportional to head displacement, but the intervals are too brief to play any role in spatial orientation. The dominant time constant for the human horizontal semicircular canals, which separate short from long stimuli, is about 5 to 10 sec. In addition to this mechanical cupular time constant, there are important neural processes that act to extend the effective time constants. One of these, known as “velocity storage” (Raphan & Cohen, 1985), maintains the ongoing subjective velocity in the absence of information to the contrary and effectively lengthens the time constant for angular velocity sensation to about 16 sec, rather than the 5 to 10 sec of the semicircular canals. Because of their different dimensions, the vertical canals have shorter time constants and lower gains than the horizontal canals. The subjective response to yaw (z-axis) rotation is about 16 sec, compared to 7 sec for pitch (y-axis) rotation (Guedry, Stockwell, & Gilson, 1971). These results, using retrospective judgment of displacement, are consistent with earlier research showing shorter time constants for pitch and roll than for yaw, based on the “subjective cupulogram” measurements of the duration of postrotation sensation of turning (Melvill-Jones, Barry, & Kowalsky 1964). For exposures to constant stimuli exceeding 20 to 30 sec, a neural adaptation becomes apparent, decreasing the response to a sustained stimulus even below the level signaled by the cupula deflection (Young & Oman, 1969). The subjective velocity during prolonged constant angular acceleration therefore not only plateaus, but also begins to decay toward zero after about 30 sec. Similarly, subjective velocity during a constant velocity turn about a vertical axis decays through zero after about 25 sec and may produce a reversal in the perceived direction of turning about 30 sec after beginning the turn.
Abnormal neural adaptation consequent to combined exposure to jet fuel and noise
Published in Journal of Toxicology and Environmental Health, Part A, 2022
Figure 1 illustrates normal neural adaptation from a representative control animal. Figure 1A shows the raw voltage trace recorded from the animal. Note the series of 4–6 peaks that constitute the voltage trace. The first peak is the CAP generated by the VIIIth craniofacial nerve, also known as the cochlear or auditory nerve (Brown and Patuzzi, 2010; Guthrie and Bhatt 2021; Rattay and Danner 2014). The remaining peaks are generated from distributed sources across the brainstem (Guthrie 2016; Guthrie et al. 2008). Figure 1B illustrates the nerve response (peak 1) from the voltage trace displayed in Figure 1A. Note that this neural response exhibits a large amplitude. Data displayed in Figure 1A and 1B were derived from the use of a stimulus presented 10 times per second (10/sec). Such stimulation is considered slow and the auditory nerve might readily respond to such a stimulus, as illustrated by the prominent voltage response. In contrast, Figure 1C and 1D demonstrate that the same nerve produces no significant response in amplitude when challenged with a stimulus that is an order-of-magnitude faster where the fast stimulus is presented 100 times per second (100/sec). The ability of the nerve to modify its response (from large to small amplitude) following a change in the stimulus (from 10/sec to 100/sec) is a stereotypical example of normal neural adaptation (Kaf et al. 2017; Liberman et al. 2016). Figure 1E-1F further illustrates this point by contrasting neural responses derived from both the slow (10/sec) and fast (100/sec) stimulus paradigms.