Quantum probability in decision making from quantum information representation of neuronal states

The recent wave of interest to modeling the process of decision making with the aid of the quantum formalism gives rise to the following question: ‘How can neurons generate quantum-like statistical data?’ (There is a plenty of such data in cognitive psychology and social science.) Our model is based on quantum-like representation of uncertainty in generation of action potentials. This uncertainty is a consequence of complexity of electrochemical processes in the brain; in particular, uncertainty of triggering an action potential by the membrane potential. Quantum information state spaces can be considered as extensions of classical information spaces corresponding to neural codes; e.g., 0/1, quiescent/firing neural code. The key point is that processing of information by the brain involves superpositions of such states. Another key point is that a neuronal group performing some psychological function F is an open quantum system. It interacts with the surrounding electrochemical environment. The process of decision making is described as decoherence in the basis of eigenstates of F. A decision state is a steady state. This is a linear representation of complex nonlinear dynamics of electrochemical states. Linearity guarantees exponentially fast convergence to the decision state

Osmotic modulation of stimulus-evoked responses in the rat supraoptic nucleus

Neural information is conveyed by action potentials along axons to downstream synaptic targets. Synapses permit functionally relevant modulation of the information transmitted by converging inputs. Previous studies have measured the amount of information associated with a given stimulus based either on spike counts or on the relative frequencies of spike sequences represented as binary strings. Here we apply information theory to the phase–interval stimulus histogram (PhISH) to measure the extent of the stimulus-evoked response using the statistical relationship between each interspike interval and its phase within the stimulus cycle. We used the PhISH as a novel approach to investigate how different osmotic states affect the flow of information through the osmoreceptor complex of the hypothalamus. The amount of information conveyed from one (afferent) element of the complex, the anteroventral region of the third ventricle (AV3V), to another (an efferent element), the supraoptic nucleus, was increased by hypertonic stimulation (intravenous mannitol, z = 4.39, P < 0.001) and decreased by hypotonic stimulation (intragastric water, z = −3.37, P < 0.001). Supraoptic responses to AV3V stimulation differed from those that follow stimulation of a hypothalamic element outside the osmoreceptor complex, the suprachiasmatic nucleus (SCN), which also projects to the supraoptic nucleus. Thus osmosensitive gain control mechanisms differentially modulate osmotically dependent and osmotically independent inputs, and enhance the osmoresponsiveness of supraoptic cells within a physiological range. The value of the novel approach is that its use is not limited to the osmoreceptor ensemble but it can be used to investigate the flow of information throughout the central nervous system

Osmotic modulation of stimulus-evoked responses in the rat supraoptic nucleus

Neural information is conveyed by action potentials along axons to downstream synaptic targets. Synapses permit functionally relevant modulation of the information transmitted by converging inputs. Previous studies have measured the amount of information associated with a given stimulus based either on spike counts or on the relative frequencies of spike sequences represented as binary strings. Here we apply information theory to the phase–interval stimulus histogram (PhISH) to measure the extent of the stimulus-evoked response using the statistical relationship between each interspike interval and its phase within the stimulus cycle. We used the PhISH as a novel approach to investigate how different osmotic states affect the flow of information through the osmoreceptor complex of the hypothalamus. The amount of information conveyed from one (afferent) element of the complex, the anteroventral region of the third ventricle (AV3V), to another (an efferent element), the supraoptic nucleus, was increased by hypertonic stimulation (intravenous mannitol, z = 4.39, P &lt; 0.001) and decreased by hypotonic stimulation (intragastric water, z = −3.37, P &lt; 0.001). Supraoptic responses to AV3V stimulation differed from those that follow stimulation of a hypothalamic element outside the osmoreceptor complex, the suprachiasmatic nucleus (SCN), which also projects to the supraoptic nucleus. Thus osmosensitive gain control mechanisms differentially modulate osmotically dependent and osmotically independent inputs, and enhance the osmoresponsiveness of supraoptic cells within a physiological range. The value of the novel approach is that its use is not limited to the osmoreceptor ensemble but it can be used to investigate the flow of information throughout the central nervous system