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Brain, neocortex and microcircuits. (A) Anatomical subdivision of the mammalian brain (sagittal section through the human brain, taken from (Drake, 2010)): medulla, pons, cerebellum, midbrain, diencephalon (thalamus and hypothalamus), and cerebral hemispheres (or telencephalon: cerebral cortex, basal ganglia, the amygdala, and the hippocampal formation and corpus callosum). (B) A series of mammalian brains (taken from (Roth and Dicke, 2005)). Humans do not have the largest brain in absolute terms and are exceeded in size by many cetaceans (whales, dolphins, porpoises and the elephants). They also do not have the most convoluted cortex. (C) The neurons of the cerebral cortex are organized in characteristic layers (adapted from (Kandel, 2000)). Left subpanel: The Golgi stain shows neuronal cell bodies and dendritic trees. The Nissl method displays cell bodies and proximal dendrites. A Weigert stain for myelinated fibers reveals the pattern of axonal distribution. Right subpanel: Different types of GABA-ergic neurons (dark gray) and putative GABA-ergic neurons (light gray) have different connections with pyramidal (P) and spiny non-pyramidal (SNP) cells in the neocortex. The GABA-ergic cells include chandelier cells (C), which terminate exclusively on the axons of other neurons, and the large and small basket cells (LB, SB), whose axons terminate mainly on other cell bodies. Double bouquet (DB) and neurogliaform cells (NG) may also be GABA-ergic. (D) Representation of the major connections in the canonical microcircuit (adapted from (da Costa and Martin, 2010)). Excitatory connections are represented by arrows and inhibitory ones as lines with round ends. Neurons from different cortical layers or brain structures are represented as circles. "Lx" labels the cortical layer where the cell body is located, "Thal" labels the thalamus and "Sub" labels other subcortical structures. 

Brain, neocortex and microcircuits. (A) Anatomical subdivision of the mammalian brain (sagittal section through the human brain, taken from (Drake, 2010)): medulla, pons, cerebellum, midbrain, diencephalon (thalamus and hypothalamus), and cerebral hemispheres (or telencephalon: cerebral cortex, basal ganglia, the amygdala, and the hippocampal formation and corpus callosum). (B) A series of mammalian brains (taken from (Roth and Dicke, 2005)). Humans do not have the largest brain in absolute terms and are exceeded in size by many cetaceans (whales, dolphins, porpoises and the elephants). They also do not have the most convoluted cortex. (C) The neurons of the cerebral cortex are organized in characteristic layers (adapted from (Kandel, 2000)). Left subpanel: The Golgi stain shows neuronal cell bodies and dendritic trees. The Nissl method displays cell bodies and proximal dendrites. A Weigert stain for myelinated fibers reveals the pattern of axonal distribution. Right subpanel: Different types of GABA-ergic neurons (dark gray) and putative GABA-ergic neurons (light gray) have different connections with pyramidal (P) and spiny non-pyramidal (SNP) cells in the neocortex. The GABA-ergic cells include chandelier cells (C), which terminate exclusively on the axons of other neurons, and the large and small basket cells (LB, SB), whose axons terminate mainly on other cell bodies. Double bouquet (DB) and neurogliaform cells (NG) may also be GABA-ergic. (D) Representation of the major connections in the canonical microcircuit (adapted from (da Costa and Martin, 2010)). Excitatory connections are represented by arrows and inhibitory ones as lines with round ends. Neurons from different cortical layers or brain structures are represented as circles. "Lx" labels the cortical layer where the cell body is located, "Thal" labels the thalamus and "Sub" labels other subcortical structures. 

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The purpose of this talk is to describe some recent progress in three aspects of statistical physics that overlap biology. The first of these represents a discovery about the real world for which we presently have no theoretical understanding.1 The second concerns the solution of a rich model of many body physics which should apply to a wide range...

Citations

... In line with experimental investigations, theoretical models of somatosensory function and algorithmic computation are crucial for understanding brain function (Bernardi et al., 2021;Brecht, 2017;Maravall and Diamond, 2014;Marr, 1982). Indeed theoretical and experimental neuroscience benefit greatly from cooperation, and together will play an integral role in finally cracking the somatosensory neural code (Panzeri et al., 2017 (Mayrhofer, 2013;O'Connor et al., 2010), visual (Burgess et al., 2017), auditory (Sanders and Kepecs, 2012), olfactory (Abraham et al., 2012;Resulaj and Rinberg, 2015) and even gustatory (Vincis et al., 2020) modalities. In many of these studies it is advantageous to restrict movement through head-fixation, which allows for controlled stimulus presentation, quantification of motor output and stability for sensitive neurophysiological recordings (Guo et al., 2014c). ...
... Mice rapidly learned to actively report left or right single-whisker stimulation side within 1 week of daily training, enabling high-throughput training and behavioural experiments. For comparison, a similar task requiring head-fixed mice to discriminate left/right vibrotactile deflections takes upwards of 6 weeks to train (Mayrhofer, 2013). Learning rates in my task more accurately match those reported for simple unilateral deflection go-nogo detection tasks, whereby mice simply have to detect and report single-whisker passive deflection via a single response (lick) channel (Sachidhanandam et al., 2013). ...
... 2AFC tasks for head-fixed rodents are notoriously difficult to train, and can require multi-stage learning protocols that span months (Burgess et al., 2017;Mayrhofer et al., 2013). However, having a task design that provides an interpretable readout of perceptual behaviour is important for assessing perceptual bias, sensitivity and lapse rate (Carandini and Churchland, 2013). ...
Thesis
The neocortex supports a rich repertoire of cognitive and behavioural functions, yet the rules, or neural ‘codes’, that determine how patterns of cortical activity drive perceptual processes remain enigmatic. Experimental neuroscientists study these codes through measuring and manipulating neuronal activity in awake behaving subjects, which allows links to be identified between patterns of neural activity and ongoing behaviour functions. In this thesis, I detail the application of novel optical techniques for simultaneously recording and manipulating neurons with cellular resolution to examine how tactile signals are processed in sparse neuronal ensembles in mouse somatosensory ‘barrel’ cortex. To do this, I designed a whisker-based perceptual decision-making task for head-fixed mice, that allows precise control over sensory input and interpretable readout of perceptual choice. Through several complementary experimental approaches, I show that task performance is exquisitely coupled to barrel cortical activity. Using two- photon calcium imaging to simultaneously record from populations of barrel cortex neurons, I demonstrate that different subpopulations of neurons in layer 2/3 (L2/3) show selectivity for contralateral and ipsilateral whisker input during behaviour. To directly test whether these stimulus-tuned groups of neurons differentially impact perceptual decision-making I performed patterned photostimulation experiments to selectively activate these functionally defined sets of neurons and assessed the resulting impact on behaviour and the local cortical network in layer 2/3. In contrast with the expected results, stimulation of sensory-coding neurons appeared to have little perceptual impact on task performance. However, activation of non- stimulus coding neurons did drive decision biases. These results challenge the conventional view that strongly sensory responsive neurons carry more perceptual weight than non-responsive sensory neurons during perceptual decision-making. Furthermore, patterned photostimulation revealed and imposed potent surround suppression in L2/3, which points to strong lateral inhibition playing a dominant role in shaping spatiotemporally sparse activity patterns. These results showcase the utility of combined patterned photostimulation methods and population calcium imaging for revealing and testing neural circuit function during sensorimotor behaviour and provide new perspectives on sensory coding in barrel cortex.