Reading the Neural Code: What do Spikes Mean for Behavior?

The present study reveals the existence of an intrinsic spatial code within neuronal spikes that predicts behavior. As rats learnt a T-maze procedural task, simultaneous changes in temporal occurrence of spikes and spike directivity are evidenced in “expert” neurons. While the number of spikes between the tone delivery and the beginning of turn phase reduced with learning, the generated spikes between these two events acquired behavioral meaning that is of highest value for action selection. Spike directivity is thus a hidden feature that reveals the semantics of each spike and in the current experiment, predicts the correct turn that the animal would subsequently make to obtain reward. Semantic representation of behavior can then be revealed as modulations in spike directivity during the time. This predictability of observed behavior based on subtle changes in spike directivity represents an important step towards reading and understanding the underlying neural code

Where is the ‘Jennifer Aniston neuron’?

It is generally believed that spike timing features (firing rate, ISI) are the main characteristics that can be related to neural code. Contrary to this common belief, spike directivity, a new measure that quantifies transient charge density dynamics within action potentials (APs) provides better results in discriminating different categories of visual object recognition. Specifically, intracranial recordings from medial temporal lobe (MTL) of epileptic patients have been analyzed using firing rate, interspike intervals and spike directivity. A comparative statistical analysis of the same spikes from four selected neurons shows that electrical micro-mapped features in neurons display higher separability to input images compared to spike timing features. If the observation vector include data from all 4 neurons then the comparative analysis shows a highly significant separation between categories for spike directivity (p=0.0023) and does not display separability for ISI (p=0.3768) and firing rate (p=0.5492). The presence of electrical micro-maps within APs suggests the existence of an intrinsic “neural code" where information regarding input images is electrically written/coded and read/decoded during AP propagation in the neuron. The occurrence of electrical micro-maps within APs reflects information communication and computation in analyzed neuron within a millisecond-level time domain of AP occurrence. This existence of a “lower level” of coding where information is processed within neurons raises questions regarding the richness and reliability of models that constrain neural code to spike timing features. Additionally, this phenomenon that occurs within APs may provide a step forward in understanding the fundamental gap between molecular description, information processing and neuronal function. Importantly, this paper confirms a new paradigm regarding neural code where information processing, computation and memory formation in the brain can be explained in terms of dynamics and interaction of electric charges

Where is the ‘Jennifer Aniston neuron’?

It is generally believed that spike timing features (firing rate, ISI) are the main characteristics that can be related to neural code. Contrary to this common belief, spike directivity, a new measure that quantifies transient charge density dynamics within action potentials (APs) provides better results in discriminating different categories of visual object recognition. Specifically, intracranial recordings from medial temporal lobe (MTL) of epileptic patients have been analyzed using firing rate, interspike intervals and spike directivity. A comparative statistical analysis of the same spikes from four selected neurons shows that electrical micro-mapped features in neurons display higher separability to input images compared to spike timing features. If the observation vector include data from all 4 neurons then the comparative analysis shows a highly significant separation between categories for spike directivity (p=0.0023) and does not display separability for ISI (p=0.3768) and firing rate (p=0.5492). The presence of electrical micro-maps within APs suggests the existence of an intrinsic “neural code" where information regarding input images is electrically written/coded and read/decoded during AP propagation in the neuron. The occurrence of electrical micro-maps within APs reflects information communication and computation in analyzed neuron within a millisecond-level time domain of AP occurrence. This existence of a “lower level” of coding where information is processed within neurons raises questions regarding the richness and reliability of models that constrain neural code to spike timing features. Additionally, this phenomenon that occurs within APs may provide a step forward in understanding the fundamental gap between molecular description, information processing and neuronal function. Importantly, this paper confirms a new paradigm regarding neural code where information processing, computation and memory formation in the brain can be explained in terms of dynamics and interaction of electric charges

Beyond Spike Timing Theory – Thermodynamics of Neuronal Computation

This paper highlights ionic fluxes as information carriers in neurons. The theoretical framework regarding information transfer is presented as changes in the thermodynamic entropy that underlie specific computations determined by ionic flow. The removal or accumulation of information is analyzed in terms of ionic mass transfer related with changes in Shannon information entropy. Specifically, information transfer occurs during an action potential (AP) via the voltage gated ion channels in membranes and the same physical mechanism can be extended to various types of synapses. Since sequential APs from a selected neuron are not alike, then every spike may transfer slightly different amounts of information during their occurrence. The average efficiency in information transfer during APs is estimated using mutual information measures and Hodgkin-Huxley model. This general scheme of ions as carriers of information represents the required physical machinery for a dynamic information transfer that is missing in the current spike-timing description