Congratulations to Sue Ann Koay, who is starting up her own group at Janelia!
How does the brain internally represent a sequence of sensory information that jointly drives a decision-making behavior? Studies of perceptual decision-making have often assumed that sensory cortices provide noisy but otherwise veridical sensory inputs to downstream processes that accumulate and drive decisions. However, sensory processing in even the earliest sensory cortices can be systematically modified by various external and internal contexts. We recorded from neuronal populations across posterior cortex as mice performed a navigational decision-making task based on accumulating randomly timed pulses of visual evidence. Even in V1, only a small fraction of active neurons had sensory-like responses time-locked to each pulse. Here, we focus on how these ‘cue-locked’ neurons exhibited a variety of amplitude modulations from sensory to cognitive, notably by choice and accumulated evidence. These task-related modulations affected a large fraction of cue-locked neurons across posterior cortex, suggesting that future models of behavior should account for such influences.
The use of Neuropixels probes for chronic neural recordings is in its infancy and initial studies leave questions about long-term stability and probe reusability unaddressed. Here, we demonstrate a new approach for chronic Neuropixels recordings over a period of months in freely moving rats. Our approach allows multiple probes per rat and multiple cycles of probe reuse. We found that hundreds of units could be recorded for multiple months, but that yields depended systematically on anatomical position. Explanted probes displayed a small increase in noise compared to unimplanted probes, but this was insufficient to impair future single-unit recordings. We conclude that cost-effective, multi-region, and multi-probe Neuropixels recordings can be carried out with high yields over multiple months in rats or other similarly sized animals. Our methods and observations may facilitate the standardization of chronic recording from Neuropixels probes in freely moving animals.
Congratulations to Lucas, who has accepted a faculty position at Northwestern University! He expects to start there in January 2021.
Neural activity throughout the cortex is correlated with perceptual decisions, but inactivation studies suggest that only a small number of areas are necessary for these behaviors. Here we used virtual reality combined with optical recording and perturbation methods to show that the number of required cortical areas and their dynamics vary across related tasks with different cognitive computations.
Congratulations to postdoc Athena Akrami, who has accepted a faculty position at the Sainsbury Wellcome Centre in London!!! She expects to start there in Fall 2018.
Congratulations to postdoc Ben Scott, who has accepted a faculty position at Boston University!!! He expects to start there in Fall 2018.
Congratulations to Athena Akrami, whose paper in Nature is now out (link here).
In this paper, Athena combined formal algorithmic behavioral analysis, optogenetic inactivations, and electrophysiological recordings in rats to show that Posterior Parietal Cortex (PPC) is specifically involved in the representation and use of prior sensory experience in Parametric Working Memory (PWM) tasks, where rats compare two sequential auditory stimuli, separated by a delay.
Here’s two fantastic pieces, both on Athena’s paper, one a News and Views piece in Nature by Prof. Laura Busse: Working memory freed from the past, and the other in Neuron by Prof. f. Miguel Maravall : Cortical Lifelogging: The Posterior Parietal Cortex as Sensory History Buffer.
Congratulations to Leenoy Meshulam, whose paper in Neuron is out (link here).
In this paper, Leenoy shows that correlation patterns in CA1 hippocampus only partially arise from place encoding. She utilizes a population-level modeling approach to uncover collective patterns of activity in CA1 neurons that substantially reflect not only position but also their internal network state states.
The Maximum entropy model introduced in the paper generates predictions that set a particualry high standard for the level of agreement and precision between theoretical predictions (by Leenoy) and experimental data (by Jeff Gauthier).
Leenoy’s paper was rated “exceptional” on Faculty of 1000 — you can read the great recommendation written by Prof. Leonard Maler here.