Abstract
Conscious awareness plays a major role in human cognition and adaptive behavior, though its function in multisensory integration is not yet fully understood, hence, questions remain: How does the brain integrate the incoming multisensory signals with respect to different external environments? How are the roles of these multisensory signals defined to adhere to the anticipated behavioral-constraint of the environment? This work seeks to articulate a novel theory on conscious multisensory integration (CMI) that addresses the aforementioned research challenges. Specifically, the well-established contextual field (CF) in pyramidal cells and coherent infomax theory (Kay et al., 1998; Kay and Phillips, 2011) is split into two functionally distinctive integrated input fields: local contextual field (LCF) and universal contextual field (UCF). LCF defines the modulatory sensory signal coming from some other parts of the brain (in principle from anywhere in space-time) and UCF defines the outside environment and anticipated behavior (based on past learning and reasoning). Both LCF and UCF are integrated with the receptive field (RF) to develop a new class of contextually-adaptive neuron (CAN), which adapts to changing environments. The proposed theory is evaluated using human contextual audio-visual (AV) speech modeling. Simulation results provide new insights into contextual modulation and selective multisensory information amplification/suppression. The central hypothesis reviewed here suggests that the pyramidal cell, in addition to the classical excitatory and inhibitory signals, receives LCF and UCF inputs. The UCF (as a steering force or tuner) plays a decisive role in precisely selecting whether to amplify/suppress the transmission of relevant/irrelevant feedforward signals, without changing the content e.g., which information is worth paying more attention to? This, as opposed to, unconditional excitatory and inhibitory activity in existing deep neural networks (DNNs), is called conditional amplification/suppression.
Highlights
What is conscious awareness? Think of a well-trained and experienced car driver who automatically identifies and follows the traffic protocols in different surrounding environments by interpreting the visual scenes directly
The firing from neuron y to succeeding neuron w in the network is according to the Poisson process, represented by the synaptic weights wy+w = ry[Py+x + Py+z + Py+u] and wy−w = ry[Py−x + Py−z + Py−u], where Py+x, Py+z, Py+u and Py−x, Py−z, Py−u represent the probabilities of excitatory and inhibitory receptive field (RF), local contextual field (LCF), and universal contextual field (UCF) signals, respectively
It is worth mentioning that the author has not claimed to know the origin of consciousness, instead, proposed a theory on its possible function in multisensory integration
Summary
What is conscious awareness? Think of a well-trained and experienced car driver who automatically identifies and follows the traffic protocols in different surrounding environments (e.g., street, highway, city centre) by interpreting the visual scenes directly (such as buildings, school etc.). The driver automatically starts utilizing visual cues to leverage the complementary strengths of both ambiguous sound (reversing-beeps) and visuals for optimized decision making These are a few examples of conscious awareness, where the external environment helps establishing the anticipated behavior and the corresponding optimal roles of incoming multisensory signals. It is observed that in noisy environments (e.g., a busy restaurant, bar, cocktail party), human brain naturally utilizes other modalities (such as lips, body language, facial expressions) to perceive speech or the conveyed message [i.e., speech-in-noise (SIN) perception] (Sumby and Pollack, 1954; McGurk and MacDonald, 1976; Summerfield, 1979; Patterson and Werker, 2003) This multimodal nature of speech is well-established in the literature; it is understood how speech is produced by the vibration of vocal folds and configuration of the articulatory organs.
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