A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded with a 24-bit EEG system with minimum bandwidth of 3.2 kHz. Custom PCBs interface with a PC to control the measurement process, electrode addressing and triggering of external stimuli. The performance of the system was characterised using resistor phantoms to represent human scalp recordings, with an SNR of 77.5 dB, stable across a four hour recording and 20 Hz to 20 kHz. In studies of both haeomorrhage using scalp electrodes, and evoked activity using epicortical electrode mats in rats, it was possible to reconstruct images matching established literature at known areas of onset. Data collected using scalp electrode in humans matched known tissue impedance spectra and was stable over frequency. The experimental procedure is software controlled and is readily adaptable to new paradigms. Where possible, commercial or open-source components were used, to minimise the complexity in reproduction. The hardware designs and software for the system have been released under an open source licence, encouraging contributions and allowing for rapid replication.

The neural representations of prior information about the state of the world are poorly understood. To investigate them, we examined brain-wide Neuropixels recordings and widefield calcium imaging collected by the International Brain Laboratory. Mice were trained to indicate the location of a visual grating stimulus, which appeared on the left or right with prior probability alternating between 0.2 and 0.8 in blocks of variable length. We found that mice estimate this prior probability and thereby improve their decision accuracy. Furthermore, we report that this subjective prior is encoded in at least 20% to 30% of brain regions which, remarkably, span all levels of processing, from early sensory areas (LGd, VISp) to motor regions (MOs, MOp, GRN) and high level cortical regions (ACAd, ORBvl). This widespread representation of the prior is consistent with a neural model of Bayesian inference involving loops between areas, as opposed to a model in which the prior is incorporated only in decision-making areas. This study offers the first brain-wide perspective on prior encoding at cellular resolution, underscoring the importance of using large scale recordings on a single standardized task.

A key challenge in neuroscience is understanding how neurons in hundreds of interconnected brain regions integrate sensory inputs with prior expectations to initiate movements and thereby make decisions. It is difficult to meet this challenge if different laboratories apply different analyses to different recordings in different regions during different behaviours. Here, we report a comprehensive set of recordings from 621733 neurons across 139 mice in 12 labs performing a decision making task with sensory, motor, and cognitive components, obtained with 699 Neuropixels probe insertions covering 279 brain areas in the left forebrain and midbrain and the right hindbrain and cerebellum. We provide an initial appraisal of this brain-wide map, assessing how neural activity encoded key task variables. Representations of visual stimuli appeared transiently in classical visual areas after stimulus onset and then spread to ramp-like activity in a collection of mid- and hindbrain regions that also encoded choices. Neural responses correlated with motor action almost everywhere in the brain. Responses to reward delivery and consumption versus negative feedback were also widespread. This publicly available dataset represents an unprecedented resource for understanding how computations distributed across and within brain areas drive behaviour.

Electrical Impedance Tomography (EIT) is an emerging technique which has been used to image evoked activity during whisker displacement in the cortex of an anaesthetised rat with a spatiotemporal resolution of 200 μm and 2 ms. The aim of this work was to extend EIT to image not only from the cortex but also from deeper structures active in somatosensory processing, specifically the ventral posterolateral (VPL) nucleus of the thalamus. The direct response in the cortex and VPL following 2 Hz forepaw stimulation were quantified using a 57-channel epicortical electrode array and a 16-channel depth electrode. Impedance changes of -0.16 ± 0.08% at 12.9 ± 1.4 ms and -0.41 ± 0.14% at 8.8±1.9 ms were recorded from the cortex and VPL respectively. For imaging purposes, two 57-channel epicortical electrode arrays were used with one placed on each hemisphere of the rat brain. Despite using parameters optimised toward measuring thalamic activity and undertaking extensive averaging, reconstructed activity was constrained to the cortical somatosensory forepaw region and no significant activity at a depth greater than 1.6 mm below the surface of the cortex could be reconstructed. An evaluation of the depth sensitivity of EIT was investigated in simulations using estimates of the conductivity change and noise levels derived from experiments. These indicate that EIT imaging with epicortical electrodes is limited to activity occurring 2.5 mm below the surface of the cortex. This depth includes the hippocampus and so EIT has the potential to image activity, such as epilepsy, originating from this structure. To image deeper activity, however, alternative methods such as the additional implementation of depth electrodes will be required to gain the necessary depth resolution.

Objective. Electrical Impedance Tomography (EIT) can image impedance changes associated with evoked physiological activity in the cerebral cortex using an array of epicortical electrodes. An impedance change is observed as the externally applied current, normally confined to the extracellular space is admitted into the conducting intracellular space during neuronal depolarisation. The response is largest at DC and decreases at higher frequencies due to capacitative transfer of current across the membrane. Biophysical modelling has shown that this effect becomes significant above 100 Hz. Recordings at DC, however, are contaminated by physiological endogenous evoked potentials. By moving to 1.7 kHz, images of somatosensory evoked responses have been produced down to 2 mm with a resolution of 2 ms and 200 µm. Hardware limitations have so far restricted impedance measurements to frequencies < 2 kHz. The purpose of this work was to establish the optimal frequency for extending EIT to image throughout the brain and to characterise the response at frequencies > 2 kHz using improved hardware. Approach. Impedance changes were recorded during forepaw somatosensory stimulation in both cerebral cortex and the VPL nucleus of the thalamus in anaesthetised rats using applied currents of 1 kHz to 10 kHz. Main results. In the cortex, impedance changed by -0.04 ± 0.02 % at 1 kHz, reached a peak of -0.13 ± 0.05 % at 1475 Hz and decreased to -0.05 ± 0.02 % at 10 kHz. At these frequencies, changes in the thalamus were -0.26 ± 0.1 %, -0.4 ± 0.15 % and -0.08 ± 0.03 % respectively. The signal-to-noise ratio (SNR) was also highest at 1475 Hz with values of 29.5 ± 8 and 31.6 ± 10 recorded from the cortex and thalamus respectively. Significance. This indicates that the optimal frequency for imaging cortical and thalamic evoked activity using fast neural EIT is 1475 Hz.

Objective. Electrical impedance tomography has the potential to image fast neural activity associated with physiological or epileptic activity throughout the brain. These applications pose a particular challenge as expected voltage changes on the electrodes are less than 1% and geometrical constraints of the body under investigation mean that electrodes can not be evenly distributed around its boundary. Unlike other applications, however, information regarding the location of expected activity is typically available. An informative method for choosing current paths that maximise sensitivity to specific regions is desirable. Approach. Two electrode addressing protocol generation methods based on current density vectors concentrated in a region of interest have been proposed. One focuses solely on maximising its magnitude while the other considers its distribution. The quality of reconstructed images using these protocols was assessed in a simulation study conducted in a human and rat mesh and compared to the protocol that maximises distance between injecting electrodes. Main results. When implementing the protocol that focused on maximising magnitude, the current density concentrated in a region of interest increased by up to a factor of 3. When the distribution of the current was maximised, the spread of current density vectors increased by up to fivefold. For the small conductivity changes expected in the applications explored, image quality was best when implementing the protocol that maximised current density. The average image error when using this protocol was 7% better than when employing other protocols. Significance. We conclude that for fast neural EIT applications, the protocol that maximises current density is the best protocol to implement.